Author: Radhey S. Singh
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 30
Book Description
Lp-norm Consistencies of Nonparametric Estimates of Regression, Heteroskedasticity and Variance of Regression Estimate when Distribution of Regressor is Known
Author: Radhey S. Singh
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 30
Book Description
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 30
Book Description
The Exact Powers of Some Autocorrelation Tests when Relevant Regressors are Omitted
Author: John P. Small
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 32
Book Description
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 32
Book Description
Bibliographie der Staats-und Wirtschaftswissenschaften
Author:
Publisher:
ISBN:
Category : Classification
Languages : en
Pages : 976
Book Description
Publisher:
ISBN:
Category : Classification
Languages : en
Pages : 976
Book Description
Bibliographie der Wirtschaftswissenschaften
Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 984
Book Description
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 984
Book Description
Optimal Telecommunications Tariffs and the CCITT
Author: Michael Carter
Publisher:
ISBN:
Category : Cartels
Languages : en
Pages : 22
Book Description
Publisher:
ISBN:
Category : Cartels
Languages : en
Pages : 22
Book Description
A Distribution-Free Theory of Nonparametric Regression
Author: László Györfi
Publisher: Springer Science & Business Media
ISBN: 0387224424
Category : Mathematics
Languages : en
Pages : 662
Book Description
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Publisher: Springer Science & Business Media
ISBN: 0387224424
Category : Mathematics
Languages : en
Pages : 662
Book Description
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Nonlinear Lp-Norm Estimation
Author: Rene Gonin
Publisher: Routledge
ISBN: 1351428179
Category : Mathematics
Languages : en
Pages : 318
Book Description
Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear LtandLo.-norm estimation problems, this important reference/text extensively delineates ahistory of Lp-norm estimation. It examines the nonlinear Lp-norm estimation problem that isa viable alternative to least squares estimation problems where the underlying errordistribution is nonnormal, i.e., non-Gaussian.Nonlinear LrNorm Estimation addresses both computational and statistical aspects ofLp-norm estimation problems to bridge the gap between these two fields . . . contains 70useful illustrations ... discusses linear Lp-norm as well as nonlinear Lt, Lo., and Lp-normestimation problems . . . provides all appropriate computational algorithms and FORTRANlistings for nonlinear Lt- and Lo.-norm estimation problems . . . guides readers with clear endof-chapter notes on related topics and outstanding research publications . . . contains numericalexamples plus several practical problems .. . and shows how the data can prescribe variousapplications of Lp-norm alternatives.Nonlinear Lp-Norm Estimation is an indispensable reference for statisticians,operations researchers, numerical analysts, applied mathematicians, biometricians, andcomputer scientists, as well as a text for graduate students in statistics or computer science.
Publisher: Routledge
ISBN: 1351428179
Category : Mathematics
Languages : en
Pages : 318
Book Description
Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear LtandLo.-norm estimation problems, this important reference/text extensively delineates ahistory of Lp-norm estimation. It examines the nonlinear Lp-norm estimation problem that isa viable alternative to least squares estimation problems where the underlying errordistribution is nonnormal, i.e., non-Gaussian.Nonlinear LrNorm Estimation addresses both computational and statistical aspects ofLp-norm estimation problems to bridge the gap between these two fields . . . contains 70useful illustrations ... discusses linear Lp-norm as well as nonlinear Lt, Lo., and Lp-normestimation problems . . . provides all appropriate computational algorithms and FORTRANlistings for nonlinear Lt- and Lo.-norm estimation problems . . . guides readers with clear endof-chapter notes on related topics and outstanding research publications . . . contains numericalexamples plus several practical problems .. . and shows how the data can prescribe variousapplications of Lp-norm alternatives.Nonlinear Lp-Norm Estimation is an indispensable reference for statisticians,operations researchers, numerical analysts, applied mathematicians, biometricians, andcomputer scientists, as well as a text for graduate students in statistics or computer science.
Efficient Estimation of the Error Distribution Function in Heteroskedastic Nonparametric Regression with Missing Data
Author: Justin Chown
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Nonparametric Regression and Spline Smoothing
Author: Randall L. Eubank
Publisher: CRC Press
ISBN: 1482273144
Category : Mathematics
Languages : en
Pages : 359
Book Description
Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for co
Publisher: CRC Press
ISBN: 1482273144
Category : Mathematics
Languages : en
Pages : 359
Book Description
Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for co
Efficient Estimation of Nonparametric Regression in the Presence of Dynamic Heteroskedasticity
Author: Oliver B. Linton
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
We study the efficient estimation of nonparametric regressions with conditional heteroskedasticity in a time series setting. We introduce a weighted local polynomial regression smoother that takes account of the dynamic heteroskedasticity. The effect of weighting on nonparametric regressions is examined, and cases when efficiency gain can be achieved via weighting is investigated. We show that in many popular nonparametric regression models our method has lower asymptotic variance than the usual unweighted procedures. A Monte Carlo investigation is conducted and confirms the efficiency gain over conventional nonparametric regression estimators in finite samples. We use our method in several common applications concerning stock returns.
Publisher:
ISBN:
Category :
Languages : en
Pages : 75
Book Description
We study the efficient estimation of nonparametric regressions with conditional heteroskedasticity in a time series setting. We introduce a weighted local polynomial regression smoother that takes account of the dynamic heteroskedasticity. The effect of weighting on nonparametric regressions is examined, and cases when efficiency gain can be achieved via weighting is investigated. We show that in many popular nonparametric regression models our method has lower asymptotic variance than the usual unweighted procedures. A Monte Carlo investigation is conducted and confirms the efficiency gain over conventional nonparametric regression estimators in finite samples. We use our method in several common applications concerning stock returns.