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X-WR-CALNAME:Institute of Applied Statistics and Data Science
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X-WR-CALDESC:Events for Institute of Applied Statistics and Data Science
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TZID:UTC
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DTSTART:20140101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20160105T153000
DTEND;TZID=UTC:20160105T170000
DTSTAMP:20170807T131731Z
CREATED:20170807T131731Z
LAST-MODIFIED:20170807T131731Z
UID:883-1452007800-1452013200@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 5\, 2016
DESCRIPTION:A Multistage Model for Prediction of Sequence of Events\n\n\nJanuary 5\, 2016 – 6:16am \n\n\n\nFull Title:\nA Multistage Model for Prediction of Sequence of Events\n\n\nSpeaker:\nRafiqul I Chowdhury\, MSc\n\n\n\nPhD candidate\, ISRT\, University of Dhaka\n\n\nDate/Time:\nTuesday\, January 5\, 2016\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nMulti-state models are most commonly used class of methods to analyze sequence of events occurring over time and generating repeated measures with censored observations. The effect of risk factors on the transition hazard from one state to another is measured using the Cox model. In recent years\, there is a growing interest to predict the disease status at different stages and endpoints. A key challenge is the simplification and generalization of the existing method for prediction for the large number of events or stages. In this research\, a simple alternative method is proposed for risk prediction of the sequence of events using multistage modelling approach. The proposed multi-state model for prediction of a future event for continuous time data may not be appropriate for the discrete time. We also developed the multistage model for discrete time based on the regressive modelling approach. The proposed method of prediction is a new development using a series of events in conditional setting arising from the beginning to the endpoint. The proposed method is based on a marginal-conditional approach to link the events occurring in a trajectory. The probability of a trajectory can be calculated easily. The main improvement of proposed method for risk prediction is that it is a simple approach\, compared to the existing ones\, and this approach can be generalized to any number of events in the process to the endpoints.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-5-2016/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150811T153000
DTEND;TZID=UTC:20150811T163000
DTSTAMP:20170807T131906Z
CREATED:20170807T131906Z
LAST-MODIFIED:20170807T131906Z
UID:885-1439307000-1439310600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, August 11\, 2015
DESCRIPTION:Survival Analysis and Phylogenetics in Infectious Disease Epidemiology\n\n\nAugust 11\, 2015 – 2:35pm \n\n\n\nFull Title:\nSurvival Analysis and Phylogenetics in Infectious Disease Epidemiology\n\n\nSpeaker:\nEben Kenah\n\n\n\nAssistant Professor of Biostatistics at the University of Florida\n\n\nDate/Time:\nTuesday\, August 11\, 2015\, 3:30pm – 4:30pm\n\n\nVenue:\nSeminar Room\, Institute of Statistical Research & Training (3rd floor)\, University of Dhaka\, Dhaka\, Bangladesh (map)\n\n\n\n  \n\nABSTRACT\nThe analysis of infectious disease transmission data is complicated because disease outcomes in different individuals are inherently dependent. We show how survival analysis provides an elegant statistical framework for handling this dependency. When who-infected-whom is observed\, standard methods from survival analysis can be used to estimate the probability of infectious contact as a function of time since the onset of infectiousness—including Cox regression modeling of covariate effects on infectiousness and susceptibility. When who-infects-whom is observed\, the likelihood for the model is a sum over all possible transmission trees. These models can be fit using an expectation-maximization (EM) algorithm. Finally\, we show how genetic sequence data from pathogen samples can be used to restrict the set of possible transmission trees\, resulting in more precise estimates of transmission parameters.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-august-11-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150528T150000
DTEND;TZID=UTC:20150528T160000
DTSTAMP:20170807T132044Z
CREATED:20170807T132044Z
LAST-MODIFIED:20170807T132044Z
UID:887-1432825200-1432828800@isrt.ac.bd
SUMMARY:Seminar on Thursday\, May 28\, 2015
DESCRIPTION:Generational transmission of cardiovascular risks\n\n\nMay 29\, 2015 – 7:54am \n\n\n\nFull Title:\nGenerational transmission of cardiovascular risks: methodological challenges\n\n\nSpeaker:\nAbdullah Al Mamun\, PhD\n\n\n\nUniversity of Queensland\nAustralia\n\n\nDate/Time:\nThursday\, May 28\, 2015\, 3:00pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nTBA
URL:https://isrt.ac.bd/event/seminar-on-thursday-may-28-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150520T153000
DTEND;TZID=UTC:20150520T170000
DTSTAMP:20170807T132214Z
CREATED:20170807T132214Z
LAST-MODIFIED:20170807T132214Z
UID:889-1432135800-1432141200@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, May 20\, 2015
DESCRIPTION:Determination of Sample Size for Phase II Clinical Trials\n\n\nMay 22\, 2015 – 8:32pm \n\n\n\nFull Title:\nDetermination of Sample Size for Phase II Clinical Trials in Multiple Sclerosis using Lesional Recovery as an Outcome Measure\n\n\nSpeaker:\nMd Mahsin\, MSc\n\n\n\nInstitute of Statistical Research and Training (ISRT)\nUniversity of Dhaka\, Bangladesh\n\n\nDate/Time:\nWednesday\, May 20\, 2015\, 3:30pm\n\n\nVenue:\nInstitute of Statistical Research & Training (3rd floor)\n\n\n\n  \n\nABSTRACT\nMultiple sclerosis (MS) is an inammatory demyelinating disease of the central nervous system. The hallmark feature of the disease is the formation of focal demyelinating lesions accompanied by myelin destruction in the white matter (WM). Magnetic resonance imaging (MRI) is used identify and visualize these lesions. Repeated MRI scanning of patients (most often monthly) over period of months has become a standard protocol for Phase II trials of experimental treatment in MS. The formation of WM lesions in MS is characterized by in ammatory demyelination and then remyelination usually occurs over several months after lesion formation. Hence\, a measure reecting lesional recovery is a promising outcome for phase II clinical trials that assess the effect of therapies intended to induce remyelination. Our objective is to provide sample sizes required to detect such an experimental treatment effect with certain statistical power. We consider a parallel group design with two arms of equal number of subjects. The study design is considered as a three level hierarchical data structure where lesions are nested within subjects and are assessed repeatedly over the study period. Variable numbers of new enhancing lesions per subject and variable numbers of measurements at before and after enhancement (depends on the time of the lesion’s appearance) are also considered. The numbers of subjects in each treatment arm necessary to obtain statistical powers of 80% or 90% are determined for different numbers (6; 9; 12) of monthly follow-up scans. A mixed-effects linear regression model is used for this sample size determination.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-may-20-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150513T153000
DTEND;TZID=UTC:20150513T170000
DTSTAMP:20170807T132341Z
CREATED:20170807T132341Z
LAST-MODIFIED:20170807T132341Z
UID:892-1431531000-1431536400@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, May 13\, 2015
DESCRIPTION:SamP2CeT: An interactive computer program\n\n\nMay 16\, 2015 – 11:01pm \n\n\n\nFull Title:\nSamP2CeT: An interactive computer program for sample size and power calculation for two-level cost-effectiveness trials\n\n\nSpeaker:\nMd. Abu Manju\, PhD\n\n\n\nDepartment of Methodology and Statistics\nCAPHRI School for Public Health and Primary Care\nMaastricht University\, Maastricht\, The Netherlands\n\n\nDate/Time:\nWednesday\, May 13\, 2015\, 3:30pm\n\n\nVenue:\nISRT seminar room\n\n\n\n  \n\nABSTRACT\nThe cost-effectiveness of interventions (e.g. new medical therapies or health care technologies) is often evaluated in randomized clinical trials-where individuals are nested within clusters\, for instance patients in general practices. In such two-level cost effectiveness trials\, one can randomly assign treatments to individuals within clusters (multicentre trial) or to entire clusters (cluster randomized trial (CRT)). Such cost-effectiveness trials (CRTs and multicentre trials) need careful planning to evaluate the cost-effectiveness of interventions within the available financial research resources. The optimal number of clusters and the optimal number of subjects per cluster for both types of cost-effectiveness trials can be determined by using optimal design theory. After presenting some theoretical results on how to calculate samples sizes for these designs\, the presentation will continue with a description of a user-friendly computer program SamP2CeT (Sample size and Power calculation for 2-level Cost-effectiveness Trials) enabling researchers to design cost-effectiveness trials with regard to the optimal number of clusters and the optimal number of subjects per cluster. In case of insufficient knowledge on model parameters\, the computer program SamP2CeT also provides numbers of clusters and numbers of subjects per cluster starting from a maximin strategy. SamP2CeT can either be used to calculate the minimum budget for a desired level of power\, or the largest power for a fixed budget. The computer program will be illustrated for two empirical studies from the literature on cost-effectiveness trials.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-may-13-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150304T153000
DTEND;TZID=UTC:20150304T170000
DTSTAMP:20170807T132512Z
CREATED:20170807T132512Z
LAST-MODIFIED:20170807T132512Z
UID:894-1425483000-1425488400@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, March 4\, 2015
DESCRIPTION:Systematic Literature Reviews and Meta-analyses\n\n\nMarch 4\, 2015 – 9:05am \n\n\n\nFull Title:\nSystematic Literature Reviews and Meta-analyses\n\n\nSpeaker:\nOlav Muurlink\, PhD\n\n\n\nCentral Queensland University\, Australia\n\n\nDate/Time:\nWednesday\, March 4\, 2015\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nThe literature review lies at the core of designing good studies. It enables the researcher to understand where the gaps in current research lies\, to guide where research should proceed. Additionally\, it can use of systematic literature reviews or meta-analyses\, to build new knowledge out of pre-existing studies. In this talk I will describe a program to assist researchers to tackle literature reviews both as the basis for their own empirical studies\, or as research outcomes in themselves.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-march-4-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150219T153000
DTEND;TZID=UTC:20150219T170000
DTSTAMP:20170807T132701Z
CREATED:20170807T132701Z
LAST-MODIFIED:20170807T132701Z
UID:896-1424359800-1424365200@isrt.ac.bd
SUMMARY:Seminar on Thursday\, February 19\, 2015
DESCRIPTION:Financial Development and Armed Conflict\n\n\nFebruary 16\, 2015 – 9:00am \n\n\n\nFull Title:\nFinancial Development and Armed Conflict: A Cross-country Analysis\n\n\nSpeaker:\nMd Rashel Hasan\, MSc\n\n\n\nChief Economist’s Unit\, Bangladesh Bank\n\n\nDate/Time:\nThursday\, February 19\, 2015\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIn this paper we have examined how armed conflict is associated with financial development and to what extent armed conflict occurrences able to explain the variations in the financial sector in a cross-country perspective. The intention is to check whether there exists any systematically different financial development outcome among developing countries due to having occurrences of armed conflict. In order to address the question\, the study exploits a panel data covering 66 developing countries for the period 1985-2010. Financial development has been measured by two proxy indicators: M2 as a share of GDP and credit allocated to private sector by banks as a share of GDP. Our findings suggest that armed conflict has significant adverse effect on financial development. In addition\, quality of governance is found highly significant and conducive to the financial development. In one hand\, governance quality appears with greater impact towards credit allocated to private sector as the effect of armed conflict seems insignificant. On the other hand\, negative effect of armed conflict towards M2 as a percentage of GDP gets smaller in absolute term in the presence of governance quality; however\, remain statistically significant. This paper also explores that the negative effect of armed conflict on M2 gets increased (in absolute term) as armed conflict intensifies. Nevertheless\, governance performances seem trading off with low and medium intensity of armed conflict implying that governance quality does matter but cannot offset entirely the effect of high intensity armed conflict and its effect by retarding M2 as a share of GDP.
URL:https://isrt.ac.bd/event/seminar-on-thursday-february-19-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150208T143000
DTEND;TZID=UTC:20150208T160000
DTSTAMP:20170813T185529Z
CREATED:20170813T185529Z
LAST-MODIFIED:20170813T185529Z
UID:1447-1423405800-1423411200@isrt.ac.bd
SUMMARY:Seminar on Sunday\, February 8\, 2015
DESCRIPTION:Are Overweight Children More Likely to Underestimate\n\n\nFebruary 2\, 2015 – 8:01am \n\n\n\nFull Title:\nAre Overweight Children More Likely to Underestimate Their Weight Status: a Novel Approach to Quantify Weight Status Misperception\n\n\nSpeaker:\nMohammad Kaviul Anam Khan\, MSc\n\n\n\nSchool of Public Health\, University of Alberta\, Canada\n\n\nDate/Time:\nSunday\, February 8\, 2015\, 2:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nDespite high prevalence of childhood overweight and obesity\, recent studies document that 70-80% of overweight children underestimate their weight status. Weight status misperception (underestimation and overestimation of weight) is conceptualized as the discrepancy between actual (measured) and self-perceived weight status. However\, quantication of weight status misperception remains challenging. To facilitate easier interpretation\, we propose a novel approach to quantify weight status misperception using Stunkard and Truby’s body rating-scale and weight status categories (according to World Health Organization cut points) from measured height and weight among grade 5 students in Nova Scotia. In this study our main focus was to investigate to what extent the overweight and obese children underestimate their weight. We used a mixed effect logistic regression\, considering school level eff ect as random. One of the key challenges while executing this model was that while using the body rating scales as the tools of misperception\, overweight and obese children had higher probabilities of underestimating their weights compared to the normal weight children\, even if the pictures were chosen randomly. To eliminate this bias\, we introduced an offset term in the model. After eliminating the bias\, overweight and obese children have 23 and 37 times higher odds respectively to underestimate their weight status compared to normal weight children. The method used in this work is an advancement as it provides estimates are more accurate compared to the previous approaches.
URL:https://isrt.ac.bd/event/seminar-on-sunday-february-8-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150128T153000
DTEND;TZID=UTC:20150128T170000
DTSTAMP:20170813T185747Z
CREATED:20170813T185747Z
LAST-MODIFIED:20170813T185747Z
UID:1449-1422459000-1422464400@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, January 28\, 2015
DESCRIPTION:An Introduction to Data Cloning Method\n\n\nJanuary 24\, 2015 – 5:23pm \n\n\n\nFull Title:\nAn Introduction to Data Cloning Method\n\n\nSpeaker:\nMohammad Kaviul Anam Khan\, MSc\n\n\n\nSchool of Public Health\, University of Alberta\, Canada\n\n\nDate/Time:\nWednesday\, January 28\, 2015\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIn the fields of epidemiology\, ecology and medical science often we encounter with hierarchical models where maximum likelihood estimation can become very challenging. Gompertz state space model and quantile regression model are such examples. The most common approach to deal with these types of hierarchical models is Bayesian inference. However\, for a small sample size Bayesian inference largely depends on the prior distribution\, which can lead to a wrong conclusion for a misspecified prior. Data cloning an alternative approach proposed by Lele\, Dennis\, and Lutscher (2007) provides maximum likelihood estimation by using Markov Chain Monte Carlo (MCMC) approach. This estimation procedure is invariant to the choice of prior distribution and thus eliminates the subjectivity of Bayesian approach. Using this method\, inferences can be drawn for very complex hierarchical models with any standard MCMC software.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-january-28-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20150114T150000
DTEND;TZID=UTC:20150114T170000
DTSTAMP:20170813T193953Z
CREATED:20170813T185950Z
LAST-MODIFIED:20170813T193953Z
UID:1451-1421247600-1421254800@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, January 14\, 2015
DESCRIPTION:Gradients in Spatial Response Surfaces\n\n\n\nJanuary 13\, 2015 – 5:18pm \n\n\n\nFull Title:\nGradients in Spatial Response Surfaces with Application to Land-Value Data\n\n\nSpeaker:\nAnandamayee Majumdar\, PhD\n\n\n\nCenter for Advanced Statistics and Econometrics\, Soochow University\, China\n\n\nDate/Time:\nWednesday\, January 14\, 2015\, 3:00pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nFor point-referenced spatial data\, we often create explanatory models that introduce regression structure with error consisting of a spatial term and a white noise term. Here we consider more flexible regression structures that allow spatially varying regression coefficients. The resulting mean becomes a spatial response surface that is a linear combination of the components of the spatially varying coefficient vector. Of possible interest in this setting would be gradients associated with the coefficient surfaces as well as the mean surface. Gradients could be sought at arbitrary points and in arbitrary directions. Extending ideas developed in earlier work\, we obtain a fully inferential approach within the Bayesian framework for examining such gradients. In particular\, we can obtain posterior distributions for any such gradient\, for the direction of maximal gradient\, and for the magnitude of the maximal gradient. The motivation for our work is the desire to examine urban land value gradients. There is considerable literature in the real estate community on economic theory\, modeling\, and data analysis relating urban land values to distance from the city center. Here we focus on gradients to such surfaces. The flexibility of our approach allows for much richer insights into the behavior of such gradients than was available previously. We illustrate by fitting a portion of Olcott’s classic Chicago land value data.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-january-14-2015/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20140630T143000
DTEND;TZID=UTC:20140630T153000
DTSTAMP:20170813T194104Z
CREATED:20170813T190211Z
LAST-MODIFIED:20170813T194104Z
UID:1453-1404138600-1404142200@isrt.ac.bd
SUMMARY:Seminar on Monday\, June 30\, 2014
DESCRIPTION:A two-­step integrated approach\n\n\n\nJune 1\, 2014 – 8:01pm \n\n\n\nFull Title:\nA two-­step integrated approach to detect differentially expressed genes in RNA-­Seq data\n\n\nSpeaker:\nMunni Begum\, PhD\n\n\n\nBall State University\, USA\n\n\nDate/Time:\nMonday\, June 30\, 2014\, 2:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nRNA‐Seq experiments produce millions of discrete sequence reads as a measure of gene expression levels\, and enable researchers to investigate complex aspects of the genomic studies. These include but not limited to identification of differentially expressed (DE) genes in two or more treatment conditions and detection of novel transcripts. One of the common assumptions of RNA-Seq data is that\, all gene counts follow an overdispersed Poisson or negative binomial (NB) distributions\, which may not be appropriate as some genes may have stable transcription levels with no overdispersion. Thus\, a more realistic assumption in RNA-Seq data is to consider two sets of genes: overdispersed and non‐overdispersed. We consider a two‐step integrated approach to detect differentially expressed (DE) genes in RNA‐Seq data using standard Poisson model for non‐overdispersed genes and NB model for overdispersed genes. We evaluate this approach using two simulated and two real RNA‐Seq data sets. We compare the performance this method with the four popular R-software packages edgeR\, DESeq\, sSeq\, and NBPSeq with their default settings. For both the simulated and real data sets\, integrated approaches perform better or at least equally well compared to the regular methods embedded in these R-packages.
URL:https://isrt.ac.bd/event/seminar-on-monday-june-30-2014/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20140515T153000
DTEND;TZID=UTC:20140515T170000
DTSTAMP:20170813T194222Z
CREATED:20170813T190425Z
LAST-MODIFIED:20170813T194222Z
UID:1455-1400167800-1400173200@isrt.ac.bd
SUMMARY:Seminar on Thursday\, May 15\, 2014
DESCRIPTION:Robustness Properties of Optimal Designs\n\n\n\nMay 12\, 2014 – 7:17pm \n\n\n\nFull Title:\nRobustness Properties of Optimal Designs with Standard and Compound Criteria\n\n\nSpeaker:\nMd. Shaddam Hossain Bagmar MSc\n\n\n\nInstitute of Statistical Research and Training (ISRT)\nUniversity of Dhaka\, Bangladesh\n\n\nDate/Time:\nThursday\, May 15\, 2014\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nExperimental design is the process of planning a study to meet the objectives of interest\, and is very important in order to ensure the right type of measurements and the power to answer the research questions of interest as efficiently as possible. For obtaining maximum efficiency\, many criteria have been proposed in the experimental design literature. Standard criteria were useful when the variance of independent errors are available and when that is not so\, the usual criteria do not have the properties that they are intended to have. Modified criteria have defined after some modifications to the standard criteria so that the resulting designs take into account the necessity of obtaining a valid estimate of error variance for proper inferences about the parameters of the model. The modified criteria\, depend on the quantiles of appropriate F-distributions for inferences\, may result in quite extreme designs that do not allow any lack-of-fit checks. Finally\, by using compound criteria\, we construct compromise designs which are efficient in terms of the properties of the information matrix and allow pure error estimation as well as lack-of fit checking. To discriminate better between different design criteria we use the robustness properties under missing observations\, different model assumptions and change in criteria. Compound designs are found as robust as standard designs in all aspect of robustness\, but we have to be careful about modified criteria to use.
URL:https://isrt.ac.bd/event/seminar-on-thursday-may-15-2014/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20140427T153000
DTEND;TZID=UTC:20140427T170000
DTSTAMP:20170813T193753Z
CREATED:20170813T190650Z
LAST-MODIFIED:20170813T193753Z
UID:1457-1398612600-1398618000@isrt.ac.bd
SUMMARY:Seminar on Sunday\, April 27\, 2014
DESCRIPTION:Female Local Government Members and Their Interactions\n\n\n\nApril 22\, 2014 – 9:50pm \n\n\n\nFull Title:\nFemale Local Government Members and Their Interactions with Community Development Workers: Learning from an Experiment in Bangladesh\n\n\nSpeaker:\nAtonu Rabbani PhD\n\n\n\nDepartment of Economics\, University of Dhaka\n\n\nDate/Time:\nSunday\, April 27\, 2014\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nCommunity organizations and associated social capital can play important roles in economic development especially when traditional market and/or state based mechanisms are weak. While community-led interventions have been found to be important factor in economic and social development\, little is known how formation of community development groups can interact with local political leaders. In this paper we will take advantage of a social experiment to shed light on empowerment of female local political leaders through an awareness building exercise and formation of women-centric community development groups. Civic engagements and knowledge building are positively associated with social development (as we show in this paper). Such factors can make a political leader more accountable and ensure delivery of socially desirable goods and services. We show that this allows the female local government members (FLGMs) to interact with community women groups (CWGs) to prioritize sanitation and hygiene related issues (the issues that were addressed in the interventions) compared to the FLGMs in the control areas. FLGMs receiving treatment are also more likely to have a “plan” to address sanitation and hygiene issues and are more likely to work with CWGs to make such plans. We also investigated other actors (namely\, volunteer groups and general public) and interaction between those actors and the FLGMs. We found a much weaker causal links in those cases. Hence\, we conclude that our results are not spurious and causal interpretations between the interventions and management outcomes are valid. To the best of our knowledge this is probably the first effort to use such framework to understand organizational and management capacities of local political leaders.
URL:https://isrt.ac.bd/event/seminar-on-sunday-april-27-2014/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20140417T033000
DTEND;TZID=UTC:20140417T050000
DTSTAMP:20170813T194525Z
CREATED:20170813T194525Z
LAST-MODIFIED:20170813T194525Z
UID:1459-1397705400-1397710800@isrt.ac.bd
SUMMARY:Seminar on Thursday\, April 17\, 2014
DESCRIPTION:Analysis of Prostate Cancer Data\n\n\nApril 7\, 2014 – 7:01am \n\n\n\nFull Title:\nAnalysis of Prostate Cancer Data at the Presence of Latent Factor: Estimation of the Treatment Effect\n\n\nSpeaker:\nAfroza Polin\, MSc\n\n\n\nDepartment of Statistics\nJagannath University\, Dhaka\, Bangladesh\n\n\nDate/Time:\nThursday\, April 17\, 2014\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIn medical and epidemiological research\, a common technique is to categorize continuous variables before evaluating its prognostic impact on the clinical trial outcome of interest. If well established cut points are not available\, then statistical techniques are used to determine the cutoff point. This study was related to a clinical trials designed to test the effectiveness of a new treatment compared to a currently used treatment for prostate cancer. Research question was to find a dichotomous latent factor\, labeled as asymptomatic and symptomatic\, based on the patients’ observed PSA level and pain score. And\, check whether the latent factor influenced the effectiveness of the new treatment. Different approaches have been considered to estimate the threshold for PSA- (i) maximum differences in treatment effect between symptomatic and asymptomatic patients\, and (ii) maximum value for goodness of fit index (likelihood\, c-index\, concordance probability estimate). Predictive ability of these techniques have been checked through cross validation\, while the first approach to estimate the threshold point gave over estimated results. Whereas\, the threshold estimation based on goodness of fit measures provides consistent result in cross validation. Along with the classical estimation technique\, Bayesian change point model has been used to estimate the PSA threshold. Cox (1972) model was used to estimate the effect of the covariates on patient’s survival time\, and the effectiveness of the new treatment among symptomatic and asymptomatic patients. The result showed similar treatment effect among the symptomatic and asymptomatic patients.
URL:https://isrt.ac.bd/event/seminar-on-thursday-april-17-2014/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130626T150000
DTEND;TZID=UTC:20130626T170000
DTSTAMP:20170813T195053Z
CREATED:20170813T195006Z
LAST-MODIFIED:20170813T195053Z
UID:1468-1372258800-1372266000@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, June 26\, 2013
DESCRIPTION:Modelling longitudinal change-point data\n\n\n\nJune 25\, 2013 – 11:58am \n\n\n\nFull Title:\nModelling longitudinal change-point data\n\n\nSpeaker:\nShahedul Ahsan Khan\, PhD\n\n\n\nUniversity of Saskachewan\, Canada\n\n\nDate/Time:\nWednesday\, June 26\, 2013\, 3pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nContinuous changepoint data may exhibit one of two types of transitions: gradual or abrupt. Modeling the trend for such data is challenging in the presence of discontinuous derivatives. Further complications arise when we have (1) longitudinal data\, and (2) samples which come from two potential populations: one with a gradual transition\, and the other abrupt. Bent-cable regression is an appealing statistical tool to model such data due to the model’s flexibility and greatly interpretable regression coefficients. We extend bent-cable methodology for longitudinal data to account for both gradual and abrupt transitions. We describe explicitly the computationally intensive Bayesian implementations; and demonstrate our methodology by a simulation study\, and with two applications: (1) assessing the transition to early hypothermia in a rat model\, and (2) understanding CFC-11 trends monitored globally.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-june-26-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130427T153000
DTEND;TZID=UTC:20130427T170000
DTSTAMP:20170813T195243Z
CREATED:20170813T195243Z
LAST-MODIFIED:20170813T195243Z
UID:1471-1367076600-1367082000@isrt.ac.bd
SUMMARY:Seminar on Saturday\, April 27\, 2013
DESCRIPTION:Unsupervised Feature Learning with Probabilistic Models\n\n\nApril 22\, 2013 – 9:41pm \n\n\n\nFull Title:\nUnsupervised Feature Learning with Probabilistic Models\n\n\nSpeaker:\nMd. Faijul Amin\, DEng\n\n\n\nKhulna University of Engineering and Technology\, Bangladesh\n\n\nDate/Time:\nSaturday\, April 27\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nBuilding intelligent system that can emulate human reasoning process has been an ultimate goal of many philosophers\, scientists\, and researchers. When artificial intelligence emerged as a field of computer science\, people thought that logic based systems may model the human reasoning process to a large extent. However\, it turns out that human sensory systems are robust to uncertainty and noise of the external environment. Consequently\, researchers have been considering probabilistic models in pursuit of building useful intelligent systems. It is this intersection where the goal of computer scientists and statisticians meets. In computer science\, these focused studies are compiled to a new subject called Machine Learning. \nIn this talk\, some recent probabilistic models\, their applications\, and limitations will be discussed with the goal of learning useful features. The motivation of feature learning stems from the research outcomes of neuroscientists. For example\, in the vision\, edges in a scene constitute the primary features for higher cognitive processes. These primary features in turn combine to form more complex features in a hierarchical manner. A class of probabilistic models called deep belief nets has been proved as the state of-the-art method for learning feature hierarchically. Several applications\, including speech recognition\, object and motion recognition\, and natural language processing will be discussed in this talk. Although empirical successes prove the modeling strengths of deep belief nets\, theoretical investigations and analysis are less explored. Furthermore\, it is important to develop new algorithms that can learn accurate distribution of the data faster. One of my goals of this talk is to discuss the possibility of carrying out joint research with the ISRT\, which is the leading statistical research institute in Bangladesh.
URL:https://isrt.ac.bd/event/seminar-on-saturday-april-27-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130413T153000
DTEND;TZID=UTC:20130413T170000
DTSTAMP:20170813T195748Z
CREATED:20170813T195748Z
LAST-MODIFIED:20170813T195748Z
UID:1473-1365867000-1365872400@isrt.ac.bd
SUMMARY:Seminar on Saturday\, April 13\, 2013
DESCRIPTION:Variable Selection with The Modified Buckley–James Method\n\n\nMarch 30\, 2013 – 6:05pm \n\n\n\nFull Title:\nVariable Selection with The Modified Buckley–James Method and The Dantzig Selector for High–dimensional Survival Data\n\n\nSpeaker:\nHasinur Rahaman Khan\, MSc\n\n\n\nUniversity of Dhaka\, Bangladesh\n\n\nDate/Time:\nSaturday\, April 13\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nWe consider variable selection techniques for high-dimensional survival data. We develop five algorithms for variable selection suitable for right censored data. The approaches can be used for parameter estimation and prediction for survival time with both low and high–dimensional data. The first two algorithms are based on a synthesis of the Buckley–James methods and the Dantzig Selector. The remaining algorithms are based on the weighted Dantzig selector where weights are obtained using the synthesis based algorithms. The algorithms are simple and scalable. The algorithms can deal with collinearity among the covariates and also among the groups of the covariates. We conduct several simulation studies and one empirical analysis with a microarray dataset. The proposed algorithms work very well for selecting sparse model or smaller variable subsets under many practical conditions.
URL:https://isrt.ac.bd/event/seminar-on-saturday-april-13-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130323T153000
DTEND;TZID=UTC:20130323T170000
DTSTAMP:20170813T195937Z
CREATED:20170813T195937Z
LAST-MODIFIED:20170813T195937Z
UID:1475-1364052600-1364058000@isrt.ac.bd
SUMMARY:Seminar on Saturday\, March 23\, 2013
DESCRIPTION:Measures to assess the predictive ability of risk models for survival data\n\n\nMarch 20\, 2013 – 12:08pm \n\n\n\nFull Title:\nA simulation study of measures to assess the predictive ability of risk models for survival data\n\n\nSpeaker:\nM. Shafiqur Rahman\, PhD\n\n\n\nUniversity of Dhaka\, Bangladesh\n\n\nDate/Time:\nSaturday\, March 23\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIn many areas of clinical settings\, risk models are often developed to predict a patients’ future health outcomes and thereafter to guide clinical management of patients. To appreciate the quality of these models in clinical predictions\, it is important to evaluate their predictive ability. Measures to assess the predictive performance of models for binary data are reasonably well developed. Despite the proposal of several measures for survival risk models\, it is still unclear which measures should be generally used in practice. This talk focuses on an investigation of a wide range of measures using a simulation study in order to make some practical recommendations. Measures were evaluated with respect to their robustness to censoring and their sensitivity to the omission of important predictors. The simulation results show that a few measures under investigation performed well in a range of scenarios while the other measures had poor performance particularly in the presence of censored data. Based on the simulation study\, some recommendations for using these measures in practice are discussed.
URL:https://isrt.ac.bd/event/seminar-on-saturday-march-23-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130225T153000
DTEND;TZID=UTC:20130225T170000
DTSTAMP:20170813T200140Z
CREATED:20170813T200140Z
LAST-MODIFIED:20170813T200140Z
UID:1477-1361806200-1361811600@isrt.ac.bd
SUMMARY:Seminar on Monday\, February 25\, 2013
DESCRIPTION:Alternatives to Extreme Value\n\n\nFebruary 16\, 2013 – 10:25am \n\n\n\nFull Title:\nAlternatives to Extreme Value: Lévy Spectral Risk Measures applied to leading stock indices\n\n\nSpeaker:\nSharif Ullah Mozumdar\, PhD\n\n\n\nDepartment of Mathematics\, University Of Dhaka\, Bangladesh\n\n\nDate/Time:\nMonday\, February 25\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nWe investigate Lévy spectral risk measures as coherent alternatives to Generalized Pareto spectral risk measures. In particular this paper conducts an empirical study on conditional distributions belonging to Generalized Hyperbolic family of Lévy processes and compares their risk-management features with traditional unconditional extreme value approach. For frequently used VaR measure\, backtesting performance of conditional and unconditional approaches is investigated. The idea is to figure out whether there is any particular model which provides minimum violation of VaR for all indices.
URL:https://isrt.ac.bd/event/seminar-on-monday-february-25-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130209T153000
DTEND;TZID=UTC:20130209T170000
DTSTAMP:20170813T202526Z
CREATED:20170813T202526Z
LAST-MODIFIED:20170813T202526Z
UID:1479-1360423800-1360429200@isrt.ac.bd
SUMMARY:Seminar on Saturday\, February 9\, 2013
DESCRIPTION:Higher-Order Asymptotic Approximations and Their Applications\n\n\nFebruary 3\, 2013 – 10:48am \n\n\n\nFull Title:\nHigher-Order Asymptotic Approximations and Their Applications\n\n\nSpeaker:\nHyung-Tae Ha\, PhD\n\n\n\nGachon University\, South Korea\n\n\nDate/Time:\nSaturday\, February 9\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nThe main interest of my research is in distribution theory\, which lies in the center of probability and statistics. It has been a challenging topic in distribution theory during last several decades to obtain probability density and distribution functions and related probabilistic quantities of complicated functions of random variables. The main approximation methods beside obtaining exact functions are Monte Carlo simulation\, numerical inversion\, higher order asymptotic approximation\, and matrix analytic distributions. In this talk\, existing higher order asymptotic approximation methods such as Edgeworth expansion and Saddlepoint approximation are discussed and three new moment based approximation methods are introduced. Their performances are compared with those of the existing methods\, and several examples show that the new moment based methods can outperform the existing techniques. The three new methods are (1) Polynomially Adjusted Approximant (PAM)\, (2) Di erentiated LogDensity Approximant (DLA)\, (3) Pade-based Transform Approximation Method (PTAM). The new methods are applied for Delta-Gamma method in nance and VaR and TVaR of aggregate losses in actuarial science.
URL:https://isrt.ac.bd/event/seminar-on-saturday-february-9-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130202T153000
DTEND;TZID=UTC:20130202T170000
DTSTAMP:20170813T202815Z
CREATED:20170813T202815Z
LAST-MODIFIED:20170813T202815Z
UID:1481-1359819000-1359824400@isrt.ac.bd
SUMMARY:Seminar on Saturday\, February 2\, 2013
DESCRIPTION:Macroeconomic Determinants and Forecasting of Stock Market Capital\n\n\nJanuary 31\, 2013 – 5:51am \n\n\n\nFull Title:\nMacroeconomic Determinants and Forecasting of Stock Market Capital: Empirical Evidence from Bangladesh\n\n\nSpeaker:\nMd. Azim Uddin\, MSc\n\n\n\nBangladesh Bank and PhD Candidate in Applied Statistics\n\n\nDate/Time:\nSaturday\, February 2\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nTo diagnosis stock market functioning the present study uses time series of monthly data from November\, 2001 to April\, 2012 for Bangladesh on the macroeconomic variables\, namely\, Stock Market Capital\, Broad Money\, Consumer Price Index\, 3-Months Treasury Bill Rate\, Industrial Production Index\, Exchange Rate\, Stock Market Turnover and Standard and Poor’s 500 Index\, collected from Dhaka Stock Exchange Ltd. and Bangladesh Bank. Main objective of the planned study is to develop statistical models for the Dynamic Relationship between Macroeconomic Variables and Stock Market Capital of Bangladesh\, in addition to\, to make the Comparison among Forecasting Models. The methodology of the study is mainly based on Vector Autoregressive (VAR) model\, Johansen-Juselius cointegration test\, Granger causality test\, Vector Error Correction Model (VECM)\, Impulse Response Function (IRF)\, Forecast Error Variance Decomposition (FEVD)\, GARCH-family models and Stochastic Parameter Model (SPM). Implications of this study include the following. (i) Investors should look at the systematic risks revealed by these macroeconomic variables when structuring their portfolios and diversification strategies. (ii) Policymakers should seek to minimize macroeconomic fluctuations considering the effect of macroeconomic variables changes on the stock market when formulating economic policy.
URL:https://isrt.ac.bd/event/seminar-on-saturday-february-2-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130121T153000
DTEND;TZID=UTC:20130121T170000
DTSTAMP:20170813T202957Z
CREATED:20170813T202957Z
LAST-MODIFIED:20170813T202957Z
UID:1483-1358782200-1358787600@isrt.ac.bd
SUMMARY:Seminar on Monday\, January 21\, 2013
DESCRIPTION:Arsenic variations in shallow groundwater\n\n\nJanuary 15\, 2013 – 8:01pm \n\n\n\nFull Title:\nArsenic variations in shallow groundwater of Bangladesh explained by generalized regression modeling\n\n\nSpeaker:\nM. Shamsudduha\, PhD\n\n\n\nUniversity College London\, UK\n\n\nDate/Time:\nMonday\, January 21\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nThe impact of widespread groundwater-fed irrigation and increased recharge on arsenic (As) mobilization in shallow (<50 m below ground level) groundwater remains unclear. A generalized regression model (GRM) has been constructed to describe observed spatial variations in As concentrations in shallow groundwater throughout Bangladesh. The GRM reveals that\, at the national scale\, an overall increase in groundwater-fed irrigation of 1 mm/yr (1985 to 1999) is associated with a 5% lower mean As concentration in shallow groundwater. A negative association is observed between As concentrations and net changes in groundwater recharge between periods prior to (1975 to 1980) and after (1995 to 1999) the development of groundwater-fed irrigation. In summary\, the study demonstrates that: (1) As concentrations are higher where the surface geology inhibits increases in groundwater recharge in response to irrigation; and (2) As concentrations are lower where recharge fluxes have increased in response to irrigation. This analysis indicates further where increases in recharge can flush mobile As from shallow groundwater in Bangladesh.
URL:https://isrt.ac.bd/event/seminar-on-monday-january-21-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130115T153000
DTEND;TZID=UTC:20130115T170000
DTSTAMP:20170813T203146Z
CREATED:20170813T203146Z
LAST-MODIFIED:20170813T203146Z
UID:1485-1358263800-1358269200@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 15\, 2013
DESCRIPTION:Item Response Theory Modelling in Analysing Rating Scale Data\n\n\nJanuary 8\, 2013 – 8:55am \n\n\n\nFull Title:\nItem Response Theory Modelling in Analysing Rating Scale Data\n\n\nSpeaker:\nAsaduzzaman Khan\, PhD\n\n\n\nThe University of Queensland and The University of New England\, Australia\n\n\nDate/Time:\nTuesday\, January 15\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nRating scales are increasingly used to perform patient assessments through graded responses on ordinal level of measurements. Outcomes measured in rating scales however provide only a rank ordering of scores where differences between scores composing the scale are unequal in terms of what is being measured. Scores from rating scales do not have an underlying number line with an equal interval and are unable to represent a true linear and continuous measurement. As such\, they may not be able to comply with many assumptions of parametric statistics\, and has the potential to produce invalid statistical inferences. This paper highlights current concerns in using total raw scores in measuring outcomes in clinical settings along with their potential solutions through using Item Response Theory (IRT) modelling. Results from a simulation study and other real life examples are examined to investigate the suitability of using parametric statistics in the rating scale scores (e.g. summative scores) and their IRT transformed scores. The findings support the use of IRT-based scores when using rating scales to measure patient progress\, which in turn can help clinical decision making to optimize patient care.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-15-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20130107T153000
DTEND;TZID=UTC:20130107T170000
DTSTAMP:20170813T203337Z
CREATED:20170813T203337Z
LAST-MODIFIED:20170813T203337Z
UID:1487-1357572600-1357578000@isrt.ac.bd
SUMMARY:Seminar on Monday\, January 7\, 2013
DESCRIPTION:A Joint Modeling Approach for Multiple Ordinal Processes\n\n\nJanuary 1\, 2013 – 10:39am \n\n\n\nFull Title:\nA joint modeling approach for multiple ordinal processes via generalized estimating equations\n\n\nSpeaker:\nAbdus S. Wahed\n\n\n\nUniversity of Pittsburgh\nPittsburgh\, PA\, USA\n\n\nDate/Time:\nMonday\, January 7\, 2013\, 3:30pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nTo be announced
URL:https://isrt.ac.bd/event/seminar-on-monday-january-7-2013/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20121211T140000
DTEND;TZID=UTC:20121211T150000
DTSTAMP:20170813T203523Z
CREATED:20170813T203523Z
LAST-MODIFIED:20170813T203523Z
UID:1489-1355234400-1355238000@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, December 11\, 2012
DESCRIPTION:Estimation of slope of a regression model when both variables have measurement error\n\n\nDecember 7\, 2012 – 10:11pm \n\n\n\nFull Title:\nEstimation of slope of a regression model when both variables have measurement error\n\n\nSpeaker:\nShahjahan Khan\, PhD\n\n\n\nUniversity of Southern Queensland\, Australia\n\n\nDate/Time:\nTuesday\, December 11\, 2012\, 2:00pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIt is well known that in the presence of equation error in the regression models any estimator based on assumed knowledge of the ratio of error variances () is biased. Although Wald’s method could deal with models that include equation error\, it lacks efficiency and subject to identifiability problem. Based on the above two methods this paper introduces a new slope estimator for regression model when both variables are subject to measurement errors and the model includes equation error. The main aim of the proposed method is to improve the efficiency of the Wald’s estimator under flexible assumption on ratio of error variance. To compare the relative efficiency of the proposed estimator with the OLS\, Wald’s and Geary’s estimators simulation studies under various assumptions are undertaken. Also included a comparison of the new estimator with the method of moments estimator when  is biased due to the presence of the equation error. The simulation results show that the proposed estimator is more consistent and efficient than the other estimators.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-december-11-2012/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20121006T120000
DTEND;TZID=UTC:20121006T130000
DTSTAMP:20170813T203718Z
CREATED:20170813T203718Z
LAST-MODIFIED:20170813T203718Z
UID:1491-1349524800-1349528400@isrt.ac.bd
SUMMARY:Seminar on Saturday\, October 6\, 2012
DESCRIPTION:Some hierarchical models for space-time data\n\n\nOctober 4\, 2012 – 6:25am \n\n\n\nFull Title:\nSome hierarchical models for space-time data\n\n\nSpeaker:\nShuvo Bakar\, PhD\n\n\n\nISRT\, University of Dhaka and CSIRO\, Australia\n\n\nDate/Time:\nSaturday\, October 6\, 2012\, 1200 noon\n\n\nVenue:\nComputer Lab (2nd Floor)\n\n\n\n  \n\nABSTRACT\nIncreasingly large volumes of space-time data are collected everywhere by mobile computing applications\, and in many of these cases temporal data are obtained by registering events\, for example telecommunication or web traffic data. Having both the spatial and temporal dimensions adds substantial complexity to data analysis and inference tasks. In this talk we discuss some hierarchical models to analyse these complex space-time data where Markov chain Monte Carlo techniques are used to make inference. We also discuss a novel method for tackling large data sets with application to daily maximum 8-hour average ground level ozone concentration data from 1997 to 2006 from a large study region in the eastern United States. Finally\, we introduce a software package “spTimer” that can model space-time data and is currently available from the R archive network.
URL:https://isrt.ac.bd/event/seminar-on-saturday-october-6-2012/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120915T120000
DTEND;TZID=UTC:20120915T130000
DTSTAMP:20170813T203854Z
CREATED:20170813T203854Z
LAST-MODIFIED:20170813T203854Z
UID:1493-1347710400-1347714000@isrt.ac.bd
SUMMARY:Seminar on Saturday\, September 15\, 2012
DESCRIPTION:Multi-class Multi-server Accumulating Priority Queue\n\n\nSeptember 12\, 2012 – 8:49pm \n\n\n\nFull Title:\nMulti-class Multi-server Accumulating Priority Queue\n\n\nSpeaker:\nAzaz Bin Sharif\, MSc\n\n\n\nUniversity of Western Ontario\, Canada\n\n\nDate/Time:\nSaturday\, September 15\, 2012\, 12:00 noon\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nThis talk presents an accumulated priority model for multi-server queues in which waiting customers accumulate priority credit at a linear rate that depends upon their priority classification. The advantage of an accumulated priority model over a classical priority queue is that the longer a customer waits\, the greater their priority – thereby ensuring a better outcome for customers of lower priority. Numerical examples illustrating the delay impact of the accumulation rates will be presented. We hope to be able to provide broad conclusions based on the numerical experiments about the nature of priority accumulation in a multi-server environment.
URL:https://isrt.ac.bd/event/seminar-on-saturday-september-15-2012/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120627T150000
DTEND;TZID=UTC:20120627T160000
DTSTAMP:20170813T204126Z
CREATED:20170813T204126Z
LAST-MODIFIED:20170813T204126Z
UID:1495-1340809200-1340812800@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, June 27\, 2012
DESCRIPTION:Modeling Healthcare Data Using Markov Decision Process\n\n\nJune 22\, 2012 – 6:26am \n\n\n\nFull Title:\nModeling Healthcare Data Using Markov Decision Process\n\n\nSpeaker:\nKumer Pial Das\, PhD\n\n\n\nLamar University\, Texas\, USA\n\n\nDate/Time:\nWednesday\, June 27\, 2012\, 3:00pm\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nA Markov decision process (MDP) is a 4-tuple (a set of states\, a set of actions\, a set of rewards\, and a transition probability function). MDPS are used to study a wide range of randomization problems. MDPs find optimal solutions to sequential and stochastic decision problems. An MDP binds previous\, current\, and future system decisions through the proper definition of system states. The use of MDPs for modeling and solving medical treatment decisions has been increased significantly in recent years. This study gives an overview of MDP models and solution techniques.We describe MDP modeling in the context of healthcare data.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-june-27-2012/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120606T120000
DTEND;TZID=UTC:20120606T130000
DTSTAMP:20170813T204306Z
CREATED:20170813T204306Z
LAST-MODIFIED:20170813T204306Z
UID:1497-1338984000-1338987600@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, June 6\, 2012
DESCRIPTION:On the Correlation and Independence Between Sample Mean and Variance\n\n\nJune 3\, 2012 – 11:52am \n\n\n\nFull Title:\nOn the Correlation and Independence Between Sample Mean and Variance\n\n\nSpeaker:\nAnwar H Joarder\, PhD\n\n\n\nDepartment of Mathematics and Statistics\nKing Fahd University of Petroleum and Minerals\nDhahran 31261\, Saudi Arabia\n\n\nDate/Time:\nWednesday\, June 6\, 2012\, 1200 noon\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nAn alternative formula for the covariance between sample mean and variance based on any probability distribution has been derived. Interesting specials cases of uncorrelation between sample mean and variance have been identified. A direct derivation of the joint moment generating function of sample mean and variance is also presented.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-june-6-2012/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20120523T103000
DTEND;TZID=UTC:20120523T113000
DTSTAMP:20170813T204441Z
CREATED:20170813T204441Z
LAST-MODIFIED:20170813T204441Z
UID:1499-1337769000-1337772600@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, May 23\, 2012
DESCRIPTION:Macroeconomic Determinants and Forecasting of Stock Market Capital\n\n\nMay 15\, 2012 – 2:47pm \n\n\n\nFull Title:\nMacroeconomic Determinants and Forecasting of Stock Market Capital: Empirical Evidence from Bangladesh\n\n\nSpeaker:\nMd. Azim Uddin\n\n\n\nStatistics Department\, Bangladesh Bank\, Dhaka\, Bangladesh\n\n\nDate/Time:\nWednesday\, May 23\, 2012\, 10:30am\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nTo diagnosis stock market functioning the present study uses time series of monthly data from November\, 2001 to April\, 2011 for Bangladesh on the macroeconomic variables\, namely\, Stock Market Capital\, Broad Money\, Consumer Price Index\, 3-Months Treasury Bill Rate and Industrial Production Index\, collected from Dhaka Stock Exchange Ltd. and Bangladesh Bank. Main objective of the planned study is to develop statistical models for the Dynamic Relationship between Macroeconomic Variables and Stock Market Capital of Bangladesh\, in addition to\, to make the Comparison among Forecasting Models. The methodology of the study is mainly based on Vector Autoregressive (VAR) model\, Granger causality test\, Johansen-Juselius cointegration test\, Vector Error Correction Model (VECM)\, Impulse Response Function (IRF)\, Forecast Error Variance Decomposition (FEVD) and Stochastic Parameter Model (SPM). Implications of this study include the following. (i) Investors should look at the systematic risks revealed by these macroeconomic variables when structuring their portfolios and diversification strategies. (ii) Policymakers should seek to minimize macroeconomic fluctuations considering the effect of macroeconomic variables changes on the stock market when formulating economic policy.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-may-23-2012/
CATEGORIES:seminar
END:VEVENT
END:VCALENDAR