lm_per_AE {PerRegMod}R Documentation

Fitting periodic coefficients regression model by using Adaptive estimation method

Description

lm_per_AE() function gives the adaptive estimation of parameters, intercept \mu_s, slope \boldsymbol{\beta}_s, and standard deviation \sigma_s, of a periodic coefficients regression model. \widehat{\boldsymbol{\theta}}_{AE} ={\widehat{\boldsymbol{\vartheta} }_{LSE} }+\frac{1}{\sqrt{n}}{\mathbf{\Gamma}}^{-1}\mathbf{\Delta}.

Usage

lm_per_AE(x,y,s)

Arguments

x

A list of independent variables with dimension p.

y

A response variable.

s

A period of the regression model.

Value

Residuals

the residuals, that is response minus fitted values

Coefficients

a named vector of coefficients

Root mean square error

The root mean square error

Examples

set.seed(6)
n=200
s=2
x1=rnorm(n,0,1.5)
x2=rnorm(n,0,0.9)
x3=rnorm(n,0,2)
x4=rnorm(n,0,1.9)
y=rnorm(n,0,2.5)
x=list(x1,x2,x3,x4)
lm_per_AE(x,y,s)

[Package PerRegMod version 4.4.3 Index]