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X-WR-CALDESC:Events for Institute of Applied Statistics and Data Science
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DTSTART:20160101T000000
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DTSTART:20150101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20180515T140000
DTEND;TZID=UTC:20180515T153000
DTSTAMP:20180515T040605Z
CREATED:20180515T040605Z
LAST-MODIFIED:20180515T040605Z
UID:2548-1526392800-1526398200@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, 15 May 2018 at 2pm
DESCRIPTION:Title: Modified Inferential Methods on Restricted Parameters in Multivariate Regression Analysis: Applications in Socio-demographic Research \nSpeaker: Sheikh Mohammad Sayem\n\n               PhD Researcher\, ISRT\n \nAbstract: Multivariate regression analysis is getting increasing attention among the socio-demographers due to the complex nature of the interdependence of the response variables. This PhD research is to carry out detailed study on restricted parameters of multivariate regression analysis with continuous\, discrete or mixed responses to seek out or develop efficient point estimation strategy and hence develop appropriate hypothesis testing procedure for hypothesis involving restricted parameters.This seminar will give a clear idea about the specific objectives of the PhD research and about the way how the objectives will be met in line of the existing literature. In this study\, a modified maximum likelihood estimation technique is primarily used for estimating restricted parameters of multivariate regression analysis with continuous responses. A Monte Carlo simulation is carried out to evaluate the performance of the estimators. The relative efficiency of the modified maximum likelihood estimator is found to be higher than the ordinary least square or maximum likelihood estimators.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-15-may-2018-at-2pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180508T140000
DTEND;TZID=UTC:20180508T150000
DTSTAMP:20180507T011847Z
CREATED:20180507T011827Z
LAST-MODIFIED:20180507T011847Z
UID:2530-1525788000-1525791600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, April 8 at 2 pm
DESCRIPTION:Title: Approximation of the Formal Bayesian Model Comparison using the Extended Conditional Predictive Ordinatecriterion\n\nSpeaker: Md. Rashedul Hoque\, Assistant Professor\, ISRT\n \nVenue and Time: ISRT seminar room\, 2 pm\n\nAbstract: The optimal method for Bayesian model comparison is the formal Bayes factor (BF)\, according to decision theory. The formal BF is computationally troublesome for more complex models. If predictive distributions under the competing models do not have a closed form\, a cross-validation idea\, called the conditional predictive ordinate (CPO) criterion can be used. In the cross-validation sense\, this is a ‘leave-out one’ approach. CPO can be calculated directly from the Monte Carlo (MC) outputs\, and the resulting Bayesian model comparison is called the pseudo-Bayes factor (PBF). We can get closer to the formal Bayesian model comparison by increasing the ‘leave-out size’\, and at ‘leave-out all’ we recover the formal BF. But\, the MC error increases with increasing ‘leave-out size’. In this study\, we examine this for linear and logistic regression models.\nOur study reveals that the Bayesian model comparison can favor a different model for PBFcompared to BF when comparing two close linear models. So\, larger ‘leave-out sizes’ are preferred which provide result close to the optimal BF. On the other hand\, MC samples based formal Bayesian model comparisons are computed with more MC error for increasing ‘leave-out sizes’; this is observed by comparing with the available closed-form results. Still\, considering a reasonable error\, we can use ‘leave-out size’ more than one instead of fixing it at one. These findings can be extended to logistic models where closed form solution is\nunavailable.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-april-8-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180424T140000
DTEND;TZID=UTC:20180424T150000
DTSTAMP:20180424T115140Z
CREATED:20180422T010527Z
LAST-MODIFIED:20180424T115140Z
UID:2468-1524578400-1524582000@isrt.ac.bd
SUMMARY:Seminar on Tuesday 24 April\, 2018 at 2 PM
DESCRIPTION:Title: Ongoing Upgrading in RMG Enterprises: Preliminary Results from a Survey\n\n\nVenue and time: ISRT seminar room\, 2 PM\n\nSpeaker: Dr. Khondaker Golam Moazzem\n               Research Director\n               Centre For Policy Dialogue (CPD) \n               Bangladesh
URL:https://isrt.ac.bd/event/seminar-on-tuesday-24-april-2018-at-2-pm/
CATEGORIES:seminar
ATTACH;FMTTYPE=image/jpeg:https://isrt.ac.bd/wp-content/uploads/2018/04/talk_ap24_2018-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180419T080000
DTEND;TZID=UTC:20180504T170000
DTSTAMP:20180423T224937Z
CREATED:20180423T040434Z
LAST-MODIFIED:20180423T224937Z
UID:2474-1524124800-1525453200@isrt.ac.bd
SUMMARY:ISRT's Indoor Games for 2018 started on the 19th of April 2018
DESCRIPTION:The Indoor Games Tournament 2018 of ISRT started with an inauguration ceremony on Thursday\, 19th of April 2018. This year Batch 21 (the current 4th year) is organizing the event. Badminton\, table tennis\, ludo\, chess\, dart throwing\, indoor cricket are some of the many exciting games. Students\, teachers and staffs are taking part in different events. More information about the event including fixtures and rules of games can be found from the following link: \nhttps://sites.google.com/isrt.ac.bd/indoorgame2018/home
URL:https://isrt.ac.bd/event/isrts-indoor-games-for-2018-started-on-the-19th-of-april-2018/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180417T140000
DTEND;TZID=UTC:20180417T153000
DTSTAMP:20180416T172613Z
CREATED:20180416T172613Z
LAST-MODIFIED:20180416T172613Z
UID:2455-1523973600-1523979000@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, April 17 at 2 pm
DESCRIPTION:Title: Evolution of Reproductive Health in Bangladesh\n \nSpeaker: Dr. Halida Hanum Akhter \n               Faculty Member \n               Bloomberg School of Public Health \n               John Hopkins University\, Baltimore\, USA\n\nVenue: ISRT seminar room\n               \n\nAbstract: \nIn Bangladesh\, the government family planning program started in 1965 and at NGO level in around 1952. The government program was a vertical program with only IUD (intra uterine device) and high dose oral pills as a pilot program. With a demonstration project on post-partum tubal ligation in four urban clinics\, under the Family Planning Board\, the program was implemented in the whole country. In 1974\, MFSTC (Mohammadpur Fertility Services and Training Center) started as a special project of Ministry of Health and Family Planning\, Then around 1978 family planning and MCH was integrated and named MCH based family planning program. Subsequently in 1994\, ICPD (International  Conference on Population and Development) also named as Cairo conference where Reproductive health concept and definition was introduced\, vetted and cosigned by 198 countries of the world. All these countries were the cosignatory of this ‘program of action’ document and agreed to introduce reproductive health in the country program. Reproductive health is a rights based approach committing to address Life Cycle approach to women’s health issues.  Since 1994\, many international instruments\, such as ICPD POA\, ICPD +5\, ICPD +15 monitored programs nationally and globally. \nThe speaker talks about the accomplishment thus far and the unfinished agenda in reproductive health in Bangladesh.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-april-17-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180410T140000
DTEND;TZID=UTC:20180410T153000
DTSTAMP:20180330T080110Z
CREATED:20180330T075816Z
LAST-MODIFIED:20180330T080110Z
UID:2413-1523368800-1523374200@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, April 10\, 2018 at 2 pm
DESCRIPTION:Title: A model for repeated binary outcomes and comparison with quasi-likelihood based approaches\n\nSpeaker: Jahida Gulshan\n                Associate Professor\, ISRT
URL:https://isrt.ac.bd/event/seminar-on-tuesday-april-10-2018-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180403T140000
DTEND;TZID=UTC:20180403T150000
DTSTAMP:20180330T080220Z
CREATED:20180318T085610Z
LAST-MODIFIED:20180330T080220Z
UID:2399-1522764000-1522767600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, April 3 at 2 pm
DESCRIPTION:Title: The Bangladesh paradox: health gains despite poverty and income inequality  \n\n\n\n\n\nSpeaker:  Dr. Ahmed Mushtaque Raza Chowdhury \n\n                Vice Chairperson\, BRAC\n                 and\n                 Professor of Clinical Population and Family Health\n                 Joseph L. Mailman School of Public Health\n                 Columbia University\, USA
URL:https://isrt.ac.bd/event/seminar-on-tuesday-april-3-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180109T140000
DTEND;TZID=UTC:20180109T153000
DTSTAMP:20180106T163145Z
CREATED:20180106T163145Z
LAST-MODIFIED:20180106T163145Z
UID:2236-1515506400-1515511800@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 9 at 2 pm
DESCRIPTION:Title: Panjer Recursion to evaluate total claim distribution recursively\n\n \nSpeaker: Dr. Abdul H. Sharif\n              Adjunct Professor\n              Mathematical Sciences Department\n              Central Connecticut State University\, USA. \n   \nAbstract: The usual method of evaluating the distribution function of the total claims incurred in a fixed period of time\, requires the computation of many convolutions of the conditional distribution of the amount of a claim given that a claim has occurred. When the expected number of claims is large\, the computation can become unwieldy even with modern large-scale electronic computers. In this presentation\, a recursive definition of the distribution of total claims is developed for a family of claim number distributions and arbitrary claim amount distributions. When the claim amount is discrete\, the recursive definition can be used to compute the distribution of total claims without the use of convolutions. This can reduce the number of required computations by several orders of magnitude for sufficiently large portfolios.\n\nFinally\, I will discuss some current research on total claim modeling. Assuming the diversified level of the audience\, the level of mathematics will be kept to probability generating function(PGF) and moment generating function (MGF).
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-9-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171219T140000
DTEND;TZID=UTC:20171219T150000
DTSTAMP:20171105T044817Z
CREATED:20171105T044808Z
LAST-MODIFIED:20171105T044817Z
UID:2051-1513692000-1513695600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, December 19 at 2 pm
DESCRIPTION:Title: Developing Public Speaking Skills in Statistical Communication\n \nSpeaker: Mohammed Shahidullah\, PhD\, MPH\n              State Demographer\n              Illinois Department of Public Health and\n              Adjunct Faculty\n              The University of Illinois\, Springfield\, USA\n    \n Abstract: Public speaking is the process or act of performing a speech to a live audience. The objective of public speaking is to inform\, persuade or to entertain the audience. It helps in skill building\, professional credibility\, networking and finding suitable jobs. As an applied statistician it is a challenge how we communicate with our audience including our students\, colleagues and consulting clients. My talk will concentrate on: Benefits of Public Speaking\, Steps in Successful Public Speaking and Resources Available to Improve Public Speaking. Toastmasters International club (www.toastmasters.org) is a great way to learn how to formulate\, express\, and sell your ideas and yourself with confidence. I will share with you my experience with this club and how it works. My recommendation will be to join such a club to improve your skills in public speaking and leadership. 
URL:https://isrt.ac.bd/event/seminar-on-tuesday-december-19-at-2-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171217T110000
DTEND;TZID=UTC:20171217T123000
DTSTAMP:20171206T021626Z
CREATED:20171206T021626Z
LAST-MODIFIED:20171206T021626Z
UID:2108-1513508400-1513513800@isrt.ac.bd
SUMMARY:Seminar on Sunday\, December 17 at 11 am
DESCRIPTION:Title: Testing equality of two normal means using combined samples of paired and unpaired data\n\nSpeaker: Professor Nizam Uddin \, Department of Statistics\, University of Central Florida\n \nAbstract: A test statistic for testing equality of two normal means when data consist of both paired and unpaired observations is proposed. The proposed test statistic is compared with two other standard methods known in the literature with respect to the type I error rate and power using simulation results.\n\nHe will also talk about the Big data analytics PhD program offered in the University of Central Florida. 
URL:https://isrt.ac.bd/event/seminar-on-sunday-december-17-at-11-am/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171212T150000
DTEND;TZID=UTC:20171212T160000
DTSTAMP:20171210T095348Z
CREATED:20171210T095238Z
LAST-MODIFIED:20171210T095348Z
UID:2112-1513090800-1513094400@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, December 12 at 3 pm
DESCRIPTION:Title: Statisticians in the Data Science Era\n\nSpeaker: Enayetur Raheem\, Data Scientist at Carolinas HealthCare System\, North Carolina\, USA\n\nAbstract: In this talk I will discuss what it really means to be a data scientist from a statistician’s perspective. In particular\, I will share my experience about the US job market for statisticians. This will give you some ideas about your future job prospects in the US and in Bangaldesh.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-december-12-at-3-pm/
LOCATION:isrt seminar room
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171128T143000
DTEND;TZID=UTC:20171128T160000
DTSTAMP:20171128T035929Z
CREATED:20171127T092148Z
LAST-MODIFIED:20171128T035929Z
UID:2085-1511879400-1511884800@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, November 28 at 2:30 pm
DESCRIPTION:Title: Business Intelligence and Data Science\n\nSpeaker: Business Intelligence team\, Grameenphone\n\nSummary: The main focus of the seminar will be- to shed some light on the current business trends\, and the challenges the industry faces in this 21st century\, and also to delineate the prospects of Business Intelligence and Data Science in Bangladesh. The sessions will be conducted by a team of 8-10 presenters/speakers from the Business Intelligence Department of Grameenphone.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-december-28-at-230-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171119T110000
DTEND;TZID=UTC:20171119T130000
DTSTAMP:20171105T044943Z
CREATED:20171105T044554Z
LAST-MODIFIED:20171105T044943Z
UID:2049-1511089200-1511096400@isrt.ac.bd
SUMMARY:Seminar on Sunday\, November 19 at 11 am
DESCRIPTION:Title: Survival Ensembles and Representative Trees for Cancer Prognostication\n \nSpeaker: Mousumi Banerjee\, PhD\n              Research Professor of Biostatistics\n              School of Public Health & Comprehensive Cancer Center\,\n              Director of Biostatistics\n              Center for Healthcare Outcomes and Policy\n              The University of Michigan\, Ann Arbor\, USA.\n    \n Abstract: Tree-based methods have become popular for analyzing right censored survival data where the primary goal is the prognostic stratification of patients. Ensemble techniques such as random forest improve the accuracy in prediction and address the instability in a single tree by growing an ensemble of trees and aggregating. However\, individual trees are lost in the forest. This talk will first provide an overview of the methodological aspects of tree-based modeling in the censored data setting. Next\, we propose a methodology for identifying the most representative trees in a forest for survival data\, based on several tree distance metrics. For any two trees\, the metrics are chosen to (1) measure similarity of the covariates used to split the trees; (2) reflect similar clustering of patients in the terminal nodes of the trees; and (3) measure similarity in predictions from the two trees. While the latter focuses on prediction\, the first two metrics focus on the architectural similarity between two trees. The most representative trees in the forest are chosen based on the average distance between a tree and all other trees in the forest. Out of bag estimate of error rate is obtained using neighborhoods of representative trees. Simulations and data examples show gains in predictive accuracy when averaging over such neighborhoods. Although our focus is on trees for censored data\, the ideas are also applicable to classification and regression trees. We illustrate our methods using data from a thyroid cancer study.
URL:https://isrt.ac.bd/event/seminar-on-sunday-november-19-at-11-pm/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171010T140000
DTEND;TZID=UTC:20171010T150000
DTSTAMP:20171009T161343Z
CREATED:20171002T165427Z
LAST-MODIFIED:20171009T161343Z
UID:1946-1507644000-1507647600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, October 10 at 2 pm
DESCRIPTION:Title: Conditional dependence in joint modelling of longitudinal non-Gaussian outcomes\n \nSpeaker: Mili Roy\, MSc\n              Research Assistant\n              Werklund School of Education\n              University of Calgary\, Canada \n   \nAbstract: The study is motivated by the limitations of conventional joint modelling strategies based\n\n\non linear and generalized linear mixed models (LMMs/GLMMs). The class of so-called Gaussian\ncopula mixed models (GCMMs)\, introduced by Wu and de Leon (2014) to generalize conventional\nLMMs/GLMMs to non-Gaussian settings\, was adopted\, and simulations were conducted to in-\nvestigate the impact of incorrectly ignoring the conditional dependence between outcomes\, given\nthe random effects\, on the performance of maximum likelihood estimates (MLEs). A variety of\nscenarios involving shared or correlated random effects were considered\, and implementation of\nthe correct and misspecied joint models was done in SAS’s PROC NLMIXED. Although MLEs of\nfixed effects were only slightly impacted by the conditional independence misspecication\, MLEs\nbased on the correct GCMM yielded generally better performances than those from the incorrect\nmodel. Data on pediatric pain (Weiss\, 2005; Withanage et al.\, 2015) were used for illustration.
URL:https://isrt.ac.bd/event/seminar-on-october-10-at-11-am/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171004T100000
DTEND;TZID=UTC:20171004T113000
DTSTAMP:20170928T054536Z
CREATED:20170928T052103Z
LAST-MODIFIED:20170928T054536Z
UID:1924-1507111200-1507116600@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, October 4 at 10 am
DESCRIPTION:Big Data: Opportunities to Explore \n\nPresenter: DataSoft Systems Bangladesh Limited
URL:https://isrt.ac.bd/event/seminar-on-wednesday-october-4-at10-am/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170821T140000
DTEND;TZID=UTC:20170821T150000
DTSTAMP:20170819T193147Z
CREATED:20170801T083324Z
LAST-MODIFIED:20170819T193147Z
UID:660-1503324000-1503327600@isrt.ac.bd
SUMMARY:Seminar on Monday\, August 21\, 2017
DESCRIPTION:Title: Spectrum sharing in cellular networks: Optimisation and post-optimisation techniques\n \nSpeaker: Md Asaduzzaman\, PhD\n              Associate Professor\n              ISRT\, University of Dhaka \n \nAbstract: \n\nDynamic spectrum sharing aims to provide secondary access to under-utilized spectrum in cellular networks. The main aim of the talk is twofold. Firstly\, the secondary operator aims to borrow spectrum bandwidths under the assumption that more spectrum resources exist considering a merchant mode. Two optimization models are proposed using stochastic and optimization models in which the secondary operator (i) spends the minimal cost to achieve the target grade of service assuming unrestricted budget or (ii) gains the maximal profit to achieve the target grade of service assuming restricted budget. Results obtained from each model are then compared with results derived from algorithms in which spectrum borrowings are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimization framework is significantly higher than heuristic counterparts. Secondly\, post-optimization performance analysis of the operators in the form of blocking probability in various scenarios is investigated to determine the probable performance gain and degradation of the secondary and primary operators respectively. We mathematically modelled the sharing agreement scenario and derive the closed form solution of blocking probabilities for each operator. Results showed how the secondary operator perform in terms of blocking probability under various offered loads and sharing capacity. 
URL:https://isrt.ac.bd/event/seminar-on-monday-august-22-2017/
LOCATION:isrt seminar room
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170807T140000
DTEND;TZID=UTC:20170807T150000
DTSTAMP:20170801T083409Z
CREATED:20170801T082912Z
LAST-MODIFIED:20170801T083409Z
UID:656-1502114400-1502118000@isrt.ac.bd
SUMMARY:Seminar on Monday\, August 7\, 2017
DESCRIPTION:Title: Energy Expenditure Prediction from Raw Accelerometer  Data: A Comparison between Linear and Nonlinear Models\n\nSpeaker: Dr. Munni Begum\n              Professor of Mathematical Sciences\n              Ball State University\, USA\n\nAbstract:\n\nThis study had three purposes\, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models\, (2) compare linear models to artificial neural network models\, and (3) compare accuracy of accelerometers placed on the hip\, thigh\, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured\, laboratory-based protocol. Participants wore accelerometers on the right hip\, right thigh\, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression\, linear mixed\, and two ANN models. EE prediction accuracy was assessed using correlations\, root mean square error (RMSE)\, and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements\, there were no significant differences for correlations or RMSE between linear regression and linear mixed models. For the thighworn accelerometer\, there were no differences in correlations or RMSE between linear and ANN models. Conversely\, one ANN had higher correlations and lower RMSE than both linear models for the hip and both ANNs had higher correlations and lower RMSE than both linear models for the wrist-worn accelerometers. For studies using wrist-worn accelerometers\, machine-learning models offer a significant improvement in EE prediction accuracy over linear models. Conversely\, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh-worn accelerometers and may be viable alternative modeling techniques for EE prediction for hip or thigh-worn accelerometers.
URL:https://isrt.ac.bd/event/seminar-on-monday-august-7-at-2-pm/
LOCATION:isrt seminar room
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170529T100000
DTEND;TZID=UTC:20170529T110000
DTSTAMP:20170807T124825Z
CREATED:20170807T124825Z
LAST-MODIFIED:20170807T124825Z
UID:856-1496052000-1496055600@isrt.ac.bd
SUMMARY:Seminar on Monday\, May 29\, 2017
DESCRIPTION:Construction of Ensembles by Exploiting the Richness of Feature Variables in High-Dimensional Data with Application in Protein Homology\n\n\nMay 23\, 2017 – 7:13pm \n\n\n\nFull Title:\nConstruction of Ensembles by Exploiting the Richness of Feature Variables in High-Dimensional Data with Application in Protein Homology\n\n\nSpeaker:\nDr. Jabed Tomal\n\n\n\nAssistant Professor\nDepartment of Computer and Mathematical Sciences\nThe University of Toronto Scarborough\, Canada.\n\n\nDate/Time:\nMonday\, May 29\, 2017\, 10 a.m.\n\n\nVenue:\nISRT seminar room\n\n\n\n  \n\nABSTRACT\nHigh-dimensional data may contain complementary subsets of useful feature variables which could bevaluable in predicting a response. In this work\, I have developed a predictionmodel which exploits the richness of information contained in the complementary subsets ofuseful feature variables in high-dimensional data. The proposed model – which is an aggregated collection of logistic regression models (LRM) – is called an ensemble\, where each constituent LRM is fitted to a subset of feature variables. An algorithm is developed to cluster the feature variables into subsets in a way that the variables in a subset are good to put together in an LRM\, and the variables in different subsets are good in separate LRMs. Each subset of variables is called a “phalanx”\, and the resulting ensemble is called an “ensemble of phalanxes (EPX).” The strength of the ensembledepends on the algorithm’s ability to identify/output strong and diverse subsets of feature variables.\nHomologous proteins are considered to havea common evolutionary origin\, i.e.\, the bearers of homologous proteins share a common ancestor. To develop an evolutionary sequence of proteins\, a scientist needs to predict their biological homogeneity. The proposed ensembleis applied to the protein homology data\, obtained from the 2004 KDD cup competition\,and used to predict biological homogeneity of proteins. In this application\, the feature variables are various scores representing structural similarity and amino acid sequence identity of proteins. Theunderlying assumption\, for model building\,is that the structural similarity and amino acid sequence identityare predictive to proteins’ biological homogeneity.As the proportion of homologous proteins is rare\, the prediction performances of theensemble are evaluated by checking its ability to rank rare homologous proteins ahead of the non-homologous proteins. While prediction performances of an EPX are competitive to contemporary state-of-the-art ensembles\, a big leap of improvement in prediction performances is achieved by aggregating two diverse EPXs obtained from optimizing two complementary evaluation metrics.Here\, the algorithm and complementary-metrics guaranteed increased strength and diversity\, respectively\, among the ensembles of phalanxes to aggregate. Importantly\, the performances of the two aggregated EPXs are robust against individual EPX when one EPX is good for detecting close homologs and the other is good for detecting distant homologs. Using parallel computing\, the proposed ensemble is shown computationally efficient as well.
URL:https://isrt.ac.bd/event/seminar-on-monday-may-29-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170517T140000
DTEND;TZID=UTC:20170517T150000
DTSTAMP:20170814T034940Z
CREATED:20170807T125348Z
LAST-MODIFIED:20170814T034940Z
UID:859-1495029600-1495033200@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, May 17\, 2017
DESCRIPTION:Assessment of predictors selected for epidemiologic risk models using automated variable selection methods\n\n\n\nMay 17\, 2017 – 12:57pm \n\n\n\nFull Title:\nAssessment of predictors selected for epidemiologic risk models using automated variable selection methods\n\n\nSpeaker:\nDr. Haider Mannan\n\n\n\nWestern Sydney University\, Australia\n\n\nDate/Time:\nWednesday\, May 17\, 2017\, 2 p.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nTBA
URL:https://isrt.ac.bd/event/seminar-on-wednesday-may-17-2017-2-p-m/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170509T140000
DTEND;TZID=UTC:20170509T153000
DTSTAMP:20170814T035014Z
CREATED:20170807T125545Z
LAST-MODIFIED:20170814T035014Z
UID:861-1494338400-1494343800@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, May 9\, 2017
DESCRIPTION:A Tutorial of Creating R Packages under Microsoft Windows\n\n\n\nApril 23\, 2017 – 11:02am \n\n\n\nFull Title:\nA Tutorial of Creating R Packages under Microsoft Windows\n\n\nSpeaker:\nDr. Md. Hasinur Rahman Khan\n\n\n\nAssociate Professor\, ISRT\n\n\nDate/Time:\nTuesday\, May 9\, 2017\, 14.00-15.30\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nCreating an R package is my hobby- a very few number of R programmers or practitioners over the world might claim this but most of them would like to love to document their R code and disseminate their research which is possible only by creating R package because creating R package forces to document own code and provide test examples to ensure that it actually works. This also becomes an ideal way of making sure others have access to own work. This talk is a tutorial of how to create an R package under Windows environment. At the end of the talk\, a demonstration with my latest R package called DNAseqtest would be presented as the guideline of gaining confidence for the potential R package builders
URL:https://isrt.ac.bd/event/seminar-on-tuesday-may-9-2017-14-00-15-30/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170214T153000
DTEND;TZID=UTC:20170214T170000
DTSTAMP:20170807T125839Z
CREATED:20170807T125839Z
LAST-MODIFIED:20170807T125839Z
UID:863-1487086200-1487091600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, February 14\, 2017
DESCRIPTION:Analyzing Repeated Measures Data using Joint Models\n\n\nFebruary 10\, 2017 – 12:47am \n\n\n\nFull Title:\nAnalyzing Repeated Measures Data using Joint Models\n\n\nSpeaker:\nJahida Gulshan\n\n\n\nAssociate Professor\, ISRT\, University of Dhaka\n\n\nDate/Time:\nTuesday\, February 14\, 2017\, 3.30 p.m.\n\n\nVenue:\nISRT seminar room\n\n\n\n  \n\nABSTRACT\nIn many studies\, categorical outcomes are measured repeatedly over time. Naturally\, those outcomes are correlated and methods based on marginal models are popular choices to analyze such data. However\, in reality\, marginal models may not provide an appropriate estimation procedure due to lack of proper specification of joint models for outcome variables for repeated measures. As an alternative to marginal approaches\, conditional models have also been developed in relatively few studies. However\, conditional models are also inadequate to address the problem of modeling correlated data. Both marginal and conditional models fail to represent the underlying dependence in correlated outcome variables. In this study\, a joint model is proposed in order to address the limitations of marginal and conditional models. A relative comparison of selected marginal approaches and the proposed model is examined for bivariate outcomes.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-february-14-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170205T153000
DTEND;TZID=UTC:20170205T170000
DTSTAMP:20170813T192237Z
CREATED:20170807T130019Z
LAST-MODIFIED:20170813T192237Z
UID:865-1486308600-1486314000@isrt.ac.bd
SUMMARY:Seminar on Sunday\, February 5\, 2017
DESCRIPTION:Challenges of Applied Statisticians: Experience from Health Sciences\n\n\n\nJanuary 31\, 2017 – 8:52am \n\n\n\nFull Title:\nChallenges of Applied Statisticians: Experience from Health Sciences\n\n\nSpeaker:\nDr Asad Khan\n\n\n\nSchool of Health and Rehabilitation Sciences in The University of Queensland\, Australia\n\n\nDate/Time:\nSunday\, February 5\, 2017\, 3.30 p.m.\n\n\nVenue:\nISRT seminar room\n\n\n\n  \n\nABSTRACT\nStatistics graduates are taught about how to solve well-defined statistical and mathematical problems\, but in the real world\, they need to be able to translate the real-life problem into a statistical problem and offer data-based solutions. As applied statisticians\, they need to have an understanding of the scientific subject area\, a solid understanding of statistics and good communication skills. In this talk\, we will also present case studies in the application of statistical modeling in health sciences.
URL:https://isrt.ac.bd/event/seminar-on-sunday-february-5-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170124T140000
DTEND;TZID=UTC:20170124T153000
DTSTAMP:20170807T130336Z
CREATED:20170807T130336Z
LAST-MODIFIED:20170807T130336Z
UID:869-1485266400-1485271800@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 24\, 2017
DESCRIPTION:Studies and career in Australia\n\n\nJanuary 22\, 2017 – 4:38pm \n\n\n\nFull Title:\nStudies and career in Australia\n\n\nSpeaker:\nDr. Shahid Ullah\n\n\n\nFlinders University\, Australia\n\n\nDate/Time:\nTuesday\, January 24\, 2017\, 2 p.m.\n\n\nVenue:\nISRT seminar Room\n\n\n\n  \n\nABSTRACT\nDr. Shahid Ullah of Flinders University\, Australia (a former faculty of ISRT) and some of his Australian colleagues would talk about the opportunities for higher studies and career in Australia.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-24-2017-2/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170124T113000
DTEND;TZID=UTC:20170124T130000
DTSTAMP:20170807T130155Z
CREATED:20170807T130155Z
LAST-MODIFIED:20170807T130155Z
UID:867-1485257400-1485262800@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 24\, 2017
DESCRIPTION:Youth Leadership for Sustainable Development\n\n\nJanuary 22\, 2017 – 8:45am \n\n\n\nFull Title:\nYouth Leadership for Sustainable Development\n\n\nSpeaker:\nDr. Atiur Rahman\n\n\n\nProfessor\nDepartment of Development Studies\nUniversity of Dhaka\n\n\nDate/Time:\nTuesday\, January 24\, 2017\, 11.30 a.m.\n\n\nVenue:\nISRT seminar room\n\n\n\n  \n\nABSTRACT\nAtiur Rahman is a Bangladeshi economist\, writer\, and banker. He served as the 10th Governor of Bangladesh Bank\, the central bank of Bangladesh. He has also been called “the banker of the poor” for his contribution in developing the Bangladeshi economy.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-24-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170110T113000
DTEND;TZID=UTC:20170110T123000
DTSTAMP:20170807T130521Z
CREATED:20170807T130521Z
LAST-MODIFIED:20170807T130521Z
UID:871-1484047800-1484051400@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, January 10\, 2017
DESCRIPTION:Regressive Models for Analysing and Predictions of Discrete Time Competing Risks from Repeated Measures\n\n\nJanuary 2\, 2017 – 7:24pm \n\n\n\nFull Title:\nRegressive Models for Analysing and Predictions of Discrete Time Competing Risks from Repeated Measures\n\n\nSpeaker:\nR. I. Chowdhury\n\n\n\nInstitute of Statistical Research and Training\, University of Dhaka\n\n\nDate/Time:\nTuesday\, January 10\, 2017\, 11.30 a.m. – 12.30 p.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nIn many cohort studies\, we may observe repeated outcomes with competing events. Events may occur within an interval or time to events itself are discrete. The occurrences of events at different stages produce a trajectory of events for study subjects. Objectives are to model such data efficiently and prediction of unconditional trajectory probabilities for a subject with specified covariate vectors. We extended the binary regressive logistic model for multinomial outcomes and proposed a framework to predict unconditional trajectory probabilities. Also\, multistate Markov model is used for the same and results are compared. The regressive modelling approach is very flexible which allows assessing the effects of past outcomes on the current one and requires to fit a single model for a stage. The proposed model is exemplified using Health and Retirement Study (HRS) data from the USA.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-january-10-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170101T120000
DTEND;TZID=UTC:20170101T130000
DTSTAMP:20170813T192529Z
CREATED:20170807T130657Z
LAST-MODIFIED:20170813T192529Z
UID:873-1483272000-1483275600@isrt.ac.bd
SUMMARY:Seminar on Sunday\, January 1\, 2017
DESCRIPTION:A few essential aspects of modern survey sampling\n\n\n\nDecember 20\, 2016 – 4:14pm \n\n\n\nFull Title:\nA few essential aspects of modern survey sampling\n\n\nSpeaker:\nArijit Chaudhuri\n\n\n\nIndian Statistical Institute\, Kolkata\n\n\nDate/Time:\nSunday\, January 1\, 2017\, 12.00 p.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nConditions on inclusion-probabilities of population units\, sample-size determination procedures\, availability of variance estimators in systematic sampling\, problem of small area estimation\, network and adaptive sampling and randomized response techniques as recognized as some of the essentials features in sampling finite populations are presented in brief.
URL:https://isrt.ac.bd/event/seminar-on-sunday-january-1-2017/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20161123T090000
DTEND;TZID=UTC:20161123T103000
DTSTAMP:20170807T130848Z
CREATED:20170807T130848Z
LAST-MODIFIED:20170807T130848Z
UID:875-1479891600-1479897000@isrt.ac.bd
SUMMARY:Seminar on Wednesday\, November 23\, 2016
DESCRIPTION:Estimating the cumulative incidence function of dynamic treatment regimes\n\n\nNovember 13\, 2016 – 8:45am \n\n\n\nFull Title:\nEstimating the cumulative incidence function of dynamic treatment regimes\n\n\nSpeaker:\nAbdus S. Wahed\, PhD\n\n\n\nProfessor and Director of PhD Graduate Program\nDepartment of Biostatistics\, Graduate School of Public Health\nEditor in chief of JSR\n130 Desoto St #7136 Parran (GSPH)\nUniversity of Pittsburgh\, Pittsburgh\, PA 15261\n\n\nDate/Time:\nWednesday\, November 23\, 2016\, 9.15 a.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nRecently personalized medicine and dynamic treatment regimes have drawn considerable attention. Dynamic treatment regimes are rules that govern the treatment of subjects depending on their intermediate responses or covariates. Two-stage randomization is a useful set-up to gather data for making inference on such regimes. Meanwhile\, the number of clinical trials involving competing risk censoring has risen\, where subjects in a study are exposed to more than one possible failure and the specific event of interest may not be observed because of competing events. We aim to compare several treatment regimes from a two-stage randomized trial on survival outcomes that are subject to competing risk censoring. The cumulative incidence function (CIF) has been widely used to quantify the cumulative probability of occurrence of the target event over time. However\, if we use only the data from those subjects who have followed a specific treatment regime to estimate the CIF\, the resulting estimator may be biased. Hence\, we propose alternative non-parametric estimators for the CIF by using inverse probability weighting\, and we provide inference procedures including procedures to compare the CIFs from two treatment regimes. We show the practicality and advantages of the proposed estimators through numerical studies.
URL:https://isrt.ac.bd/event/seminar-on-wednesday-november-23-2016/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20161108T153000
DTEND;TZID=UTC:20161108T170000
DTSTAMP:20170807T131132Z
CREATED:20170807T131132Z
LAST-MODIFIED:20170807T131132Z
UID:877-1478619000-1478624400@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, November 8\, 2016
DESCRIPTION:Demystifying ‘Big Data’\n\n\nNovember 3\, 2016 – 1:24pm \n\n\n\nFull Title:\nDemystifying ‘Big Data’\n\n\nSpeaker:\nDr Syed Faisal Hasan\n\n\n\nAssociate Professor of Computer Science and Engineering\, Dhaka University\n\n\nDate/Time:\nTuesday\, November 8\, 2016\, 3.30-4.45\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nNow-a-days ‘Big Data’ is one of the much talked about topics. Although data analysis is an indispensable part of modern business\, with the exponential proliferation of Internet based transactions\, social interactions\, location based services and amenities both the scale of available data and possibilities of deriving unforeseen information through data analysis is unprecedented. Therefore\, it is very important to have a firm grasp about the technology and tools that companies are using to collect\, store and analyze these large volume of data sets known as ‘big data’. This talk will provide a high level overview of ‘big data’ analysis explaining briefly about how some of the very successful companies like Uber\, Netflix\, Target etc have integrated ‘Big Data’ analysis in their day to day business. The key infrastructure/software components behind ‘big data’ will be presented. Later on the talk will finish by illustrating the capabilities and suitability of python for ‘big data’ analysis.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-november-8-2016/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20160524T153000
DTEND;TZID=UTC:20160524T170000
DTSTAMP:20170807T131256Z
CREATED:20170807T131256Z
LAST-MODIFIED:20170807T131256Z
UID:879-1464103800-1464109200@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, May 24\, 2016
DESCRIPTION:Comparison of adaptive designs for dose finding in phase I clinical trials\n\n\nMay 20\, 2016 – 3:45pm \n\n\n\nFull Title:\nComparison of adaptive designs for dose finding in phase I clinical trials\n\n\nSpeaker:\nDr. M. Iftakhar Alam\n\n\n\nInstitute of Statistical Research and Training\, University of Dhaka\, Dhaka-1000\, Bangladesh\n\n\nDate/Time:\nTuesday\, May 24\, 2016\, 3:30 p.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nThe Continual reassessment method is a model based procedure that has been in the literature to determine the maximum tolerated dose in phase I clinical trials. The maximum tolerated dose can also be found under the framework of D-optimum design. This paper investigates the two methods to explore any potential differences between them. Simulation studies for six plausible dose-response scenarios show that the D-optimum design can work well over the continual reassessment method in many cases. The D-optimum design has also been found to allocate doses from the extremes of design region to the patients in a trial. \nKeywords: Dose finding studies; Phase I trial; Maximum tolerated dose; Continual re-assessment method; D-optimum design.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-may-24-2016/
CATEGORIES:seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20160426T113000
DTEND;TZID=UTC:20160426T130000
DTSTAMP:20170807T131548Z
CREATED:20170807T131548Z
LAST-MODIFIED:20170807T131548Z
UID:881-1461670200-1461675600@isrt.ac.bd
SUMMARY:Seminar on Tuesday\, April 26\, 2016
DESCRIPTION:Some Models on Diffusion of Innovations\n\n\nApril 24\, 2016 – 4:10pm \n\n\n\nFull Title:\nSome Models on Diffusion of Innovations\n\n\nSpeaker:\nDr. Md. Abud Darda\n\n\n\nAssociate Professor of Statistics\, Natural Science Academic Group\, National University\, Gazipur 1704.\n\n\nDate/Time:\nTuesday\, April 26\, 2016\, 11:30 a.m.\n\n\nVenue:\nISRT Seminar Room\n\n\n\n  \n\nABSTRACT\nDiffusion of innovations models formulates an attempt to study the behavior of agents in the complex network structure\, contagion of information and the related consequences. Pioneering approach by F. Bass (1969) is further developed with numerous research works. Later\, considerations bring to the introduction of heterogeneity effect and marketing mix variables to the models.Empirical results show that the basic Bass model and its generalizations (GBM) can be studied as a modified form of the basic Logistic model. Recent work by Bemmaor(1994) explains the diffusion dynamics as a mixture of probability distributions obtained from individual level heterogeneity. In this presentation\, we will make a short introduction to the diffusion models and also discuss a special heterogeneous agent based diffusion modelling at the aggregate level. Examples also given to explain the natural gas production and their reserves estimates in South Asian countries in terms of the technological diffusion of innovation.
URL:https://isrt.ac.bd/event/seminar-on-tuesday-april-26-2016/
CATEGORIES:seminar
END:VEVENT
END:VCALENDAR