Learn R Programming

plmm (version 0.1-1)

Partially Linear Mixed Effects Model

Description

This package fits the partially linear mixed effects model (semiparametric random intercept model) using kernel regression, without distributional assumptions for the random terms. Estimation procedure is an iterative generalized least squares type. A nonparametric heteroskedastic variance function is allowed for the regression error. Bootstrap resampling is provided for inference. The package implements bandwidth selection by an alternative cross validation for correlated data.

Copy Link

Version

Install

install.packages('plmm')

Monthly Downloads

10

Version

0.1-1

License

GPL (>= 2)

Maintainer

OHINATA Ren

Last Published

November 28th, 2012

Functions in plmm (0.1-1)

plmm-package

Partially Linear Mixed Effects Model
plmm.bs

Bootstrap Inference
summary

Summary of a Fitted Partially Linear Mixed Effects Model.
wplmm

Weighted Partially Linear Mixed Effects Model
plot

Nonparametric Function Plot
select.h0

Bandwidths Selection for Model Reduction
coef

Extract Fixed Regression Coefficients
var.plot

Nonparametric Variance Function Estimation and Plotting
ranef

Random Effects Prediction
residuals

Extract Model Residuals
predict

Conditional or Unconditional Model Prediction
fitted

Extract Model Fitted Values
summary.bs.plmm

Summary of the bootstrap estimates of the sampling distribution.
plmm

Partially Linear Mixed Effects Model
plmm.data

Data Set for the Package Examples