Fit.class-class: S4 class for the estimation results in the mixed SDE with...

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

Description

S4 class for the estimation results in the mixed SDE with random effects in the drift, in the diffusion or both

Slots

model

'OU' or 'CIR' (character)

drift.random

0, 1, 2, or c(1,2) (numeric)

diffusion.random

0 or 1 (numeric)

gridf

matrix of values on which the estimation of the density of the random effects in the drift is done (matrix)

gridg

matrix of values on which the estimation of the density of the random effects in the diffusion is done (matrix)

mu

estimator of the mean mu of the drift random effects (numeric)

omega

estimator of the variance of the drift random effects (numeric)

a

estimator of the shape of the Gamma distribution for the diffusion random effect (numeric)

lambda

estimator of the scale of the Gamma distribution for the diffusion random effect (numeric)

sigma2

estimated value of σ^2 if the diffusion coefficient is not random (numeric)

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 (matrix)

estimpsi2

vector of the estimator of the diffusion random effects σ_j^2 (numeric)

estimf

estimator of the (conditional) density of the drift random effects (numeric)

estimg

estimator of the density of σ_j^2 (numeric)

estim.drift.fix

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

estim.diffusion.fix

1 if the user asked for the estimation of fixed diffusion coefficient (numeric)

discrete

1 if the estimation is based on the likelihood of discrete observations, 0 otherwise (numeric)

bic

bic (numeric)

aic

aic (numeric)

times

vector of observation times, storage of input variable (numeric)

X

matrix of observations, storage of input variable (matrix)

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