The Partially Linear Regression Model: Monte Carlo Evidence from the Projection Pursuit Regression Approach

نویسندگان

  • Dingding Li
  • Thanasis Stengos
چکیده

In a partially linear regression model with a high dimensional unknown component we find an estimator of the parameter of the linear part based on projection pursuit methods to be considerably more efficient than the standard density weighted kernel estimator.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Positive-Shrinkage and Pretest Estimation in Multiple Regression: A Monte Carlo Study with Applications

Consider a problem of predicting a response variable using a set of covariates in a linear regression model. If it is a priori known or suspected that a subset of the covariates do not significantly contribute to the overall fit of the model, a restricted model that excludes these covariates, may be sufficient. If, on the other hand, the subset provides useful information, shrinkage meth...

متن کامل

A Monte Carlo simulation technique for assessment of earthquake-induced displacement of slopes

The dynamic response of slopes against earthquake is commonly characterized by the earthquake-induced displacement of slope (EIDS). The EIDS value is a function of several variables such as the material properties, slope geometry, and earthquake acceleration. This work is aimed at the prediction of EIDS using the Monte Carlo simulation method (MCSM). Hence, the parameters height, unit specific ...

متن کامل

Projection Estimators for Generalized Linear Models

We introduce a new class of robust estimators for generalized linear models which is an extension of the class of projection estimators for linear regression. These projection estimators are defined using an initial robust estimator for a generalized linear model with only one unknown parameter. We found a bound for the maximum asymptotic bias of the projection estimator caused by a fraction ε ...

متن کامل

Projection pursuit regression for moderate non-linearities

We present methods specially designed to be effective with moderately non-linear regression relationships. The model fitted is of the Projection Pursuit Regression (PPR) type with a smooth, non-parametric link function connecting the mean response to a linear combination of the regressors. New algorithms, close to ordinary linear regression, are developed. Considerable numerical evidence is giv...

متن کامل

Robust inference in high- dimensional approximately sparse quantile regression models

This work proposes new inference methods for the estimation of a regression coefficientof interest in quantile regression models. We consider high-dimensional models where the number ofregressors potentially exceeds the sample size but a subset of them suffice to construct a reasonableapproximation of the unknown quantile regression function in the model. The proposed methods are<lb...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001