Author: Arthur Lewbel
Publisher:
ISBN:
Category :
Languages : en
Pages : 37
Book Description
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x) + e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides estimators of m(x) and its derivatives. The convergence rate is the same as for an uncensored nonparametric regression and its derivatives. We also provide root n estimates of weighted average derivatives of m(x), which equal the coefficients in linear or partly linearr specifications for m(x). An extension permits estimation in the presence of a general form of heteroscedasticity. We also extend the estimator to the nonparametric truncated regression model, in which only uncensored data points are observed. The estimators are based on the relationship ?E(yk x)/?m(x) = kE[yk-1/(y gt; 0)x ], which we show holds for positive integers k.
Nonparametric Censored and Truncated Regression
Author: Arthur Lewbel
Publisher:
ISBN:
Category :
Languages : en
Pages : 37
Book Description
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x) + e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides estimators of m(x) and its derivatives. The convergence rate is the same as for an uncensored nonparametric regression and its derivatives. We also provide root n estimates of weighted average derivatives of m(x), which equal the coefficients in linear or partly linearr specifications for m(x). An extension permits estimation in the presence of a general form of heteroscedasticity. We also extend the estimator to the nonparametric truncated regression model, in which only uncensored data points are observed. The estimators are based on the relationship ?E(yk x)/?m(x) = kE[yk-1/(y gt; 0)x ], which we show holds for positive integers k.
Publisher:
ISBN:
Category :
Languages : en
Pages : 37
Book Description
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x) + e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides estimators of m(x) and its derivatives. The convergence rate is the same as for an uncensored nonparametric regression and its derivatives. We also provide root n estimates of weighted average derivatives of m(x), which equal the coefficients in linear or partly linearr specifications for m(x). An extension permits estimation in the presence of a general form of heteroscedasticity. We also extend the estimator to the nonparametric truncated regression model, in which only uncensored data points are observed. The estimators are based on the relationship ?E(yk x)/?m(x) = kE[yk-1/(y gt; 0)x ], which we show holds for positive integers k.
Nonparametric Regression for Censored and Truncated Data
Author: Chul-Ki Kim
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 174
Book Description
Nonparametric and Parametric Estimation with Truncated Regression Data
Author: Kwok-Leung Tsui
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
Book Description
Regression Models
Author: Richard Breen
Publisher: SAGE
ISBN: 9780803957107
Category : Mathematics
Languages : en
Pages : 92
Book Description
This book provides an introduction to the regression models needed, where an outcome variable for a sample is not representative of the population from which a generalized result is sought.
Publisher: SAGE
ISBN: 9780803957107
Category : Mathematics
Languages : en
Pages : 92
Book Description
This book provides an introduction to the regression models needed, where an outcome variable for a sample is not representative of the population from which a generalized result is sought.
Least Absolute Deviations Estimation for Censored and Truncated Regression Models
Author: James Leo Powell
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 262
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 262
Book Description
Nonparametric Function Estimation with Left-truncated and Right-censored Data
Author: Jinho Park
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
Book Description
Nonparametric Estimation and Regression Analysis with Left Truncated and Right Censored Data
Author: Stanford University. Dept. of Statistics
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 23
Book Description
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 23
Book Description
Analysis of Doubly Truncated Data
Author: Achim Dörre
Publisher: Springer
ISBN: 9811362416
Category : Mathematics
Languages : en
Pages : 109
Book Description
This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.
Publisher: Springer
ISBN: 9811362416
Category : Mathematics
Languages : en
Pages : 109
Book Description
This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.
A Nonparametric Approach to the Truncated Regression Problem
Author: Kwok-Leung Tsui
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages :
Book Description
Least Absolute Deviations Estimation for Censored and Truncated Regression Models
Author: James Leo Powell III
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description