T
Tathagata Banerjee
Researcher at Indian Institute of Management Ahmedabad
Publications - 34
Citations - 312
Tathagata Banerjee is an academic researcher from Indian Institute of Management Ahmedabad. The author has contributed to research in topics: Regression analysis & Estimator. The author has an hindex of 10, co-authored 34 publications receiving 300 citations. Previous affiliations of Tathagata Banerjee include University of Calcutta.
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Exploring Multivariate Data With the Forward Search
TL;DR: Besides advocating the use of differencing procedures as simple methods for nonparametric and semiparametric regression analysis, the author appliesNonparametric least squares methods to take generalnonparametric constraints into account.
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Bayesian analysis of generalized odds-rate hazards models for survival data
TL;DR: A class of nonproportional hazards models known as generalized odds-rate class of regression models, which is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and accelerated life time model are considered.
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Analysis of Two-Way Layout of Count Data Involving Multiple Counts in Each Cell
TL;DR: In this paper, the authors developed C(α) tests for interaction and main effects assuming data to be Poisson distributed and also assuming that data within the cells have extra (over/under) dispersion beyond that explained by a Poisson distribution.
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Measurement error model for misclassified binary responses
TL;DR: The article considers regression models for binary response in a situation when the response is subject to classification error and it is assumed that some of the covariates are unobservable, but measurements on its surrogates are available.
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Optimal factorial designs for cDNA microarray experiments
TL;DR: In this paper, the authors consider cDNA microarray experiments when the cell populations have a factorial structure, and investigate the problem of their optimal designing under a baseline parametrization where the objects of interest differ from those under the more common orthogonal parameter.