Model checking in Tobit regression via nonparametric smoothing

Model Checking in Tobit Regression Model via Nonparametric Smoothing

A nonparametric lack-of-fit test is proposed to check the adequacy of the presumed parametric form for the regression function in Tobit regression models by applying Zheng’s device with weighted residuals. It is shown that testing the null hypothesis for the standard Tobit regression models is equivalent to test a new null hypothesis of the classic regression models. An optimal weight function ...

Title Model Checking and Variable Selection in Nonparametric Regression

February 19, 2015 Type Package Title Model Checking and Variable Selection in Nonparametric Regression Version 1.0 Date 2012-08-03 Author Adriano Zanin Zambom Maintainer Adriano Zanin Zambom Depends R (>= 2.15.0), dr, MASS, graphics Description This package provides tests of significance for covariates (or groups of covariates) in a fully nonparametric regression mode...

A simple nonparametric test for diagnosing nonlinearity in Tobit median regression model

In many applications, the response variable is observed only when it is above or below a given threshold otherwise the threshold itself is observed. Tobit median regression model is a useful semiparametric procedure for analyzing this type of censored data. We propose a simple nonparametric test for assessing the common linearity assumption in this model. Compared to those existing methods in t...

Review : Nonparametric Simple Regression : Smoothing Scatterplots

Tobit model estimation and sliced inverse regression

It is not unusual for the response variable in a regression model to be subject to censoring or truncation. Tobit regression models are specific examples of such a situation, where for some observations the observed response is not the actual response, but the censoring value (often zero), and an indicator that censoring (from below) has occurred. It is well-known that the maximum likelihood es...