The Propensity Score Adjustment method was originally developed to construct weights by estimating response probabilities and using them in Horvitz–Thompson type estimators. This method is usually used by combining a non-probability sample with a reference sample to construct propensity models for the non-probability sample. Calibration can be used in a posterior way to adding information of auxiliary variables.

Imports: caret, sampling, e1071, glmnet, Matrix

Description: Function and data sets in the book entitled "Nonlinear Time Series Analysis with R Applications" B.Guris (2020). The book will be published in Turkish and the original name of this book will be "R Uygulamali Dogrusal Olmayan Zaman Serileri Analizi". It is possible to perform nonlinearity tests, nonlinear unit root tests, nonlinear cointegration tests and estimate nonlinear error correction models by using the functions written in this package. The Momentum Threshold Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and the Self Exciting Threshold Autoregressive (SETAR) type unit root tests can be performed using the functions written. In addition, cointegration tests using the Momentum Threshold Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and the Self Exciting Threshold Autoregressive (SETAR) models can be applied. It is possible to estimate nonlinear error correction models. The Granger causality test performed using nonlinear models can also be applied.

Package: NonpModelCheck
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 <adriano.zambom@gmail.com>
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
model and a variable (or group) selection procedure based on
False Discovery Rate. In addition, it provides a function for
local polynomial regression for any number of dimensions, using
a bandwidth specified by the user or automatically chosen by
cross validation or an adaptive procedure.
License: GPL (>= 2)
Packaged: 2012-09-21 17:36:56 UTC; adrianozambom
Repository: CRAN
Date/Publication: 2012-09-22 04:33:51