predReg: Bayesian prediction in mixed nonlinear regression models

In SimoneHermann/hierRegSDE:

Description

Bayesian prediction in the mixed nonlinear regression model y_{ij}= f(φ_j, t_{ij}) + ε_{ij}, ε_{ij}~N(0,γ^2*s^2(t_{ij}), φ_j~N(μ, Ω).

Usage

predReg(t, samples, fODE, sVar, cand, len = 1000, mod = "Gompertz")

Arguments

t	vector of times which are predicted
samples	list of samples from the posterior
fODE	regression function
sVar	variance function
cand	vector of candidates for trajection sampling
len	number of samples from the predictive distribution
mod	model out of Gompertz, Richards, logistic, Weibull, only used instead of fODE

Value

matrix of predictions in t

SimoneHermann/hierRegSDE documentation built on May 9, 2019, 1:46 p.m.