EM_parameter_sd: Bootstrap Parameter Inference

In EMSNM: EM Algorithm for Sigmoid Normal Model

Description

Estimating the parameters and their stand error through the sorted parameters estimated by bootstrap method.

Usage

EM_parameter_sd(EMsimulation_sort_alpha, EMsimulation_sort_eta, EMsimulation_sort_sigma)

Arguments

EMsimulation_sort_alpha	sorted alpha estimated by bootstrap method.
EMsimulation_sort_eta	sorted eta estimated by bootstrap method.
EMsimulation_sort_sigma	sorted sigma estimated by bootstrap method.

Value

sigma	the estimation of sigma
sigma_sd	the estimation of standard error of sigma
alpha	the estimation of alpha
alpha_sd	the estimation of standard error of alpha
eta	the estimation of eta
eta_sd	the estimation of standard error of eta

Author(s)

Linsui Deng

Examples

#parameter initialization
etasize <- 2
classsize <- 2
alphasize <- 3
samplesize <- 100
expriments <- 30
  
etatest <- matrix(c(1,1,
                    0,0),etasize,classsize)

alphatest <- matrix(c(1,0,2,
                      4,3,5),alphasize,classsize)
sigmatest <- 0.5

EMsimulation_result <- EMsimulation(eta=etatest,alpha=alphatest,sigma=sigmatest,
                            samplesize=samplesize,expriments=expriments,
                            compact_flag=TRUE,C0=5,C1=0.5,C2=5)
index <- which(EMsimulation_result$sigma<0.8)
EMsimulation_result_sort <- EM_result_sort(EMsimulation_result$alpha[index,,],
                                            EMsimulation_result$eta[index,,])
#test of EM_parameter_sd
EM_parameter <- EM_parameter_sd(EMsimulation_result_sort$alpha,
                                EMsimulation_result_sort$eta,
                                EMsimulation_result$sigma[index])

EMSNM documentation built on May 2, 2019, 1:41 p.m.