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Contemporary Developments in Statistical Theory: A Festschrift for Hira Lal Koul

2014., 2013

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Uniformly root-N consistent density estimators for weakly dependent invertible linear processes

The Annals of statistics, 2007-04, Vol.35 (2), p.815-843

2007

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Tests for normality based on density estimators of convolutions

Statistics & probability letters, 2011-02, Vol.81 (2), p.337-343

2011

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Root-n consistent density estimators of convolutions in weighted L1 -norms

Journal of statistical planning and inference, 2007-06, Vol.137 (6), p.1765-1774

2007

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Inference about the slope in linear regression: an empirical likelihood approach

Annals of the Institute of Statistical Mathematics, 2019-02, Vol.71 (1), p.181-211

2019

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THE TRANSFER PRINCIPLE: A TOOL FOR COMPLETE CASE ANALYSIS

The Annals of statistics, 2012-12, Vol.40 (6), p.3031-3049

2012

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Estimating the innovation distribution in nonlinear autoregressive models

Annals of the Institute of Statistical Mathematics, 2002, Vol.54 (2), p.245-260

2002

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Convergence rates of density estimators for sums of powers of observations

Metrika, 2009-03, Vol.69 (2-3), p.249-264

2009

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Asymptotically Uniformly Most Powerful Tests in Parametric and Semiparametric Models

The Annals of statistics, 1996-04, Vol.24 (2), p.841-861

1996

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Estimating the error distribution function in semiparametric additive regression models

Journal of statistical planning and inference, 2012-02, Vol.142 (2), p.552-566

2012

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Prediction in moving average processes

Journal of statistical planning and inference, 2008-03, Vol.138 (3), p.694-707

2008

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Improved Density Estimators for Invertible Linear Processes: Recent Advances in Theory and Applications of Statistics

Communications in statistics. Theory and methods, 2009, Vol.38 (16-17), p.3123-3147

2009

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Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes

Statistics & probability letters, 2006-10, Vol.76 (16), p.1756-1760

2006

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Prediction in invertible linear processes

Statistics & probability letters, 2007-07, Vol.77 (12), p.1322-1331

2007

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Plug-in estimators for higher-order transition densities in autoregression

Probability and statistics, 2009-01, Vol.13, p.135-151

2009

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Improving efficient marginal estimators in bivariate models with parametric marginals

Statistics & probability letters, 2009-12, Vol.79 (23), p.2437-2442

2009

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A note on the construction of asymptotically linear estimators

Journal of statistical planning and inference, 1987, Vol.16 (1), p.89-105

Schick, Anton

1987

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Estimating the inter-arrival time density of Markov renewal processes under structural assumptions on the transition distribution

Statistics & probability letters, 2011-02, Vol.81 (2), p.277-282

2011

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Estimating the error distribution function in nonparametric regression with multivariate covariates

Statistics & probability letters, 2009-04, Vol.79 (7), p.957-964

2009

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Some Developments in Semiparametric Statistics

Journal of statistical theory and practice, 2008-01, Vol.2 (3), p.475-491

2008

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Consistency of the GMLE with Mixed Case Interval-Censored Data

Scandinavian journal of statistics, 2000-03, Vol.27 (1), p.45-55

2000

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On Efficient Estimation in Regression Models

The Annals of statistics, 1993-09, Vol.21 (3), p.1486-1521

Schick, Anton

1993

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Root n consistent and optimal density estimators for moving average processes

Scandinavian journal of statistics, 2004-03, Vol.31 (1), p.63-78

2004

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Efficient Prediction for Linear and Nonlinear Autoregressive Models

The Annals of statistics, 2006-10, Vol.34 (5), p.2496-2533

2006

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Estimating Invariant Laws of Linear Processes by U-Statistics

The Annals of statistics, 2004-04, Vol.32 (2), p.603-632

2004

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Contemporary Developments in Statistical Theory: A Festschrift for Hira Lal Koul

Uniformly root-N consistent density estimators for weakly dependent invertible linear processes

Tests for normality based on density estimators of convolutions

Root-n consistent density estimators of convolutions in weighted L1 -norms

Inference about the slope in linear regression: an empirical likelihood approach

THE TRANSFER PRINCIPLE: A TOOL FOR COMPLETE CASE ANALYSIS

Estimating the innovation distribution in nonlinear autoregressive models

Convergence rates of density estimators for sums of powers of observations

Asymptotically Uniformly Most Powerful Tests in Parametric and Semiparametric Models

Estimating the error distribution function in semiparametric additive regression models

Prediction in moving average processes

Improved Density Estimators for Invertible Linear Processes: Recent Advances in Theory and Applications of Statistics

Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes

Prediction in invertible linear processes

Plug-in estimators for higher-order transition densities in autoregression

Improving efficient marginal estimators in bivariate models with parametric marginals

A note on the construction of asymptotically linear estimators

Estimating the inter-arrival time density of Markov renewal processes under structural assumptions on the transition distribution

Estimating the error distribution function in nonparametric regression with multivariate covariates

Some Developments in Semiparametric Statistics

Consistency of the GMLE with Mixed Case Interval-Censored Data

On Efficient Estimation in Regression Models

Root n consistent and optimal density estimators for moving average processes

Efficient Prediction for Linear and Nonlinear Autoregressive Models

Estimating Invariant Laws of Linear Processes by U-Statistics

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