Probal Chaudhuri | Indian Statistical Institute, Calcutta (original) (raw)

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Papers by Probal Chaudhuri

Research paper thumbnail of On data depth and distribution-free discriminant analysis using separating surfaces

Research paper thumbnail of SiZer for Exploration of Structures in Curves

Journal of the American Statistical Association, Sep 1, 1999

Research paper thumbnail of On detection and assessment of statistical significance of Genomic Islands

BMC Genomics, Apr 1, 2008

Research paper thumbnail of Stationarity and mixing properties of replicating character strings

Research paper thumbnail of Statistical analysis of large DNA sequences using distribution of DNA words

Research paper thumbnail of On a likelihood-based approach in nonparametric smoothing and cross-validation

Statistics & Probability Letters, 1995

A likelihood-based generalization of usual kernel and nearest-neighbor-type smoothing techniques ... more A likelihood-based generalization of usual kernel and nearest-neighbor-type smoothing techniques and a related extension of the least-squares leave-one-out cross-validation are explored in a generalized regression set up. Several attractive features of the procedure are discussed and asymptotic properties of the resulting nonparametric function estimate are derived under suitable regularity conditions. Large sample performance of likelihood-based leave-one-out cross validation is investigated

Research paper thumbnail of Probabilistic Search Algorithms

Research paper thumbnail of BioSuite: A comprehensive bioinformatics software package (A unique industry-academia collaboration)

Research paper thumbnail of On estimators of the mean of infinite dimensional data in finite populations

Research paper thumbnail of Depth Regression with Application to Functional Data

arXiv (Cornell University), Jul 20, 2017

Research paper thumbnail of Convergence Rates for Kernel Regression in Infinite Dimensional Spaces

arXiv (Cornell University), Oct 31, 2016

Research paper thumbnail of The deepest point for distributions in infinite dimensional spaces

Statistical Methodology, Sep 1, 2014

Research paper thumbnail of A Wilcoxon-Mann-Whitney-type test for infinite-dimensional data

Research paper thumbnail of On data depth in infinite dimensional spaces

Annals of the Institute of Statistical Mathematics, Jul 3, 2013

Research paper thumbnail of On average derivative quantile regression

Annals of Statistics, Apr 1, 1997

Research paper thumbnail of Multi-sample comparison using spatial signs for infinite dimensional data

Electronic Journal of Statistics, 2022

Research paper thumbnail of Paired Sample Tests in Infinite Dimensional Spaces

Research paper thumbnail of Tests for high-dimensional data based on means, spatial signs and spatial ranks

Annals of Statistics, Apr 1, 2017

Research paper thumbnail of A Comparison of Estimators of Mean and Its Functions in Finite Populations

Research paper thumbnail of Depth based inference on conditional distribution with infinite dimensional data

arXiv: Methodology, 2019

We develop inference and testing procedures for conditional dispersion and skewness in a nonparam... more We develop inference and testing procedures for conditional dispersion and skewness in a nonparametric regression setup based on statistical depth functions. The methods developed can be applied in situations, where the response is multivariate and the covariate is a random element in a metric space. This includes regression with functional covariate as a special case. We construct measures of the center, the spread and the skewness of the conditional distribution of the response given the covariate using depth based nonparametric regression procedures. We establish the asymptotic consistency of those measures and develop a test for heteroscedasticity and a test for conditional skewness. We present level and power study for the tests in several simulated models. The usefulness of the methodology is also demonstrated in a real dataset. In that dataset, our responses are the nutritional contents of different meat samples measured by their protein, fat and moisture contents, and the fu...

Research paper thumbnail of On data depth and distribution-free discriminant analysis using separating surfaces

Research paper thumbnail of SiZer for Exploration of Structures in Curves

Journal of the American Statistical Association, Sep 1, 1999

Research paper thumbnail of On detection and assessment of statistical significance of Genomic Islands

BMC Genomics, Apr 1, 2008

Research paper thumbnail of Stationarity and mixing properties of replicating character strings

Research paper thumbnail of Statistical analysis of large DNA sequences using distribution of DNA words

Research paper thumbnail of On a likelihood-based approach in nonparametric smoothing and cross-validation

Statistics & Probability Letters, 1995

A likelihood-based generalization of usual kernel and nearest-neighbor-type smoothing techniques ... more A likelihood-based generalization of usual kernel and nearest-neighbor-type smoothing techniques and a related extension of the least-squares leave-one-out cross-validation are explored in a generalized regression set up. Several attractive features of the procedure are discussed and asymptotic properties of the resulting nonparametric function estimate are derived under suitable regularity conditions. Large sample performance of likelihood-based leave-one-out cross validation is investigated

Research paper thumbnail of Probabilistic Search Algorithms

Research paper thumbnail of BioSuite: A comprehensive bioinformatics software package (A unique industry-academia collaboration)

Research paper thumbnail of On estimators of the mean of infinite dimensional data in finite populations

Research paper thumbnail of Depth Regression with Application to Functional Data

arXiv (Cornell University), Jul 20, 2017

Research paper thumbnail of Convergence Rates for Kernel Regression in Infinite Dimensional Spaces

arXiv (Cornell University), Oct 31, 2016

Research paper thumbnail of The deepest point for distributions in infinite dimensional spaces

Statistical Methodology, Sep 1, 2014

Research paper thumbnail of A Wilcoxon-Mann-Whitney-type test for infinite-dimensional data

Research paper thumbnail of On data depth in infinite dimensional spaces

Annals of the Institute of Statistical Mathematics, Jul 3, 2013

Research paper thumbnail of On average derivative quantile regression

Annals of Statistics, Apr 1, 1997

Research paper thumbnail of Multi-sample comparison using spatial signs for infinite dimensional data

Electronic Journal of Statistics, 2022

Research paper thumbnail of Paired Sample Tests in Infinite Dimensional Spaces

Research paper thumbnail of Tests for high-dimensional data based on means, spatial signs and spatial ranks

Annals of Statistics, Apr 1, 2017

Research paper thumbnail of A Comparison of Estimators of Mean and Its Functions in Finite Populations

Research paper thumbnail of Depth based inference on conditional distribution with infinite dimensional data

arXiv: Methodology, 2019

We develop inference and testing procedures for conditional dispersion and skewness in a nonparam... more We develop inference and testing procedures for conditional dispersion and skewness in a nonparametric regression setup based on statistical depth functions. The methods developed can be applied in situations, where the response is multivariate and the covariate is a random element in a metric space. This includes regression with functional covariate as a special case. We construct measures of the center, the spread and the skewness of the conditional distribution of the response given the covariate using depth based nonparametric regression procedures. We establish the asymptotic consistency of those measures and develop a test for heteroscedasticity and a test for conditional skewness. We present level and power study for the tests in several simulated models. The usefulness of the methodology is also demonstrated in a real dataset. In that dataset, our responses are the nutritional contents of different meat samples measured by their protein, fat and moisture contents, and the fu...

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