Mixture.fit.class-class: S4 class for the estimation results when the random effects...

In MsdeParEst: Parametric Estimation in Mixed-Effects Stochastic Differential Equations

Description

S4 class for the estimation results when the random effects in the drift follow mixture of normal distributions

Slots

model

character 'OU' or 'CIR'

drift.random

numeric 1, 2, or c(1,2)

gridf

matrix of values on which the estimation of the density of the random effects is done

mu

array estimated value of the mean of the drift random effects at each iteration of the EM algorithm (Niter x nb.mixt x 2)

omega

array estimated value of the standard deviation of the drift random effects at each iteration of the EM algorithm (Niter x nb.mixt x 2)

mixt.prop

matrix estimated value of the mixing proportions at each iteration of the EM algorithm (Niter x nb.mixt)

sigma2

numeric estimated value of σ^2

index

index of the valid trajectories for the considered model (numeric)

indexestim

index of the trajectories used for the estimation (numeric)

estimphi

matrix of the estimator of the drift random effects

probindi

matrix of posterior component probabilities

estimf

matrix estimator of the density of the drift random effects

estim.drift.fix

numeric 1 if the user asked for the estimation of fixed parameter in the drift

bic

numeric bic

aic

numeric aic

times

vector of observation times, storage of input variable

X

matrix of observations, storage of input variable

MsdeParEst documentation built on May 2, 2019, 3:01 a.m.