sd_estimation_for_each_s {PerRegMod} | R Documentation |
Estimating periodic variances in a periodic coefficients regression model
Description
sd_estimation_for_each_s() function gives the estimation of variances, \widehat{\sigma}_s^2=\frac{1}{m-p-1}\sum\limits_{\underset{ }{r=0}}^{m-1}\widehat{\varepsilon}^2_{s+Sr}
for all s=1,...,S
,in a periodic coefficients regression model.
Usage
sd_estimation_for_each_s(x,y,s,beta_hat)
Arguments
x |
A list of independent variables with dimension |
y |
A response variable. |
s |
A period of the regression model. |
beta_hat |
The least squares estimation using LSE_Reg_per. |
Value
returns the value of \widehat{\sigma}_s^2
.
Examples
set.seed(6)
n=400
s=4
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)
beta_hat=LSE_Reg_per(x,y,s)$beta
sd_estimation_for_each_s(x,y,s,beta_hat)
[Package PerRegMod version 4.4.3 Index]