saem.fit: Fit an SAEM model

Description Usage Arguments Details Author(s)

View source: R/saem_fit.R

Description

Fit an SAEM model using either closed-form solutions or ODE-based model definitions

Usage

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saem.fit(model, data, inits, PKpars = NULL, pred = NULL, covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

saem(model, data, inits, PKpars = NULL, pred = NULL, covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

## S3 method for class 'fit.nlmixr.ui.nlme'
saem(model, data, inits, PKpars = NULL,
  pred = NULL, covars = NULL, mcmc = list(niter = c(200, 300), nmc = 3, nu
  = c(2, 2, 2)), ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1,
  transitAbs = 0), distribution = c("normal", "poisson", "binomial"),
  seed = 99)

## S3 method for class 'fit.function'
saem(model, data, inits, PKpars = NULL, pred = NULL,
  covars = NULL, mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

## S3 method for class 'fit.nlmixrUI'
saem(model, data, inits, PKpars = NULL, pred = NULL,
  covars = NULL, mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

## S3 method for class 'fit.RxODE'
saem(model, data, inits, PKpars = NULL, pred = NULL,
  covars = NULL, mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

## S3 method for class 'fit.default'
saem(model, data, inits, PKpars = NULL, pred = NULL,
  covars = NULL, mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1, transitAbs = 0),
  distribution = c("normal", "poisson", "binomial"), seed = 99)

Arguments

model

an RxODE model or lincmt()

data

input data

inits

initial values

PKpars

PKpars function

pred

pred function

covars

Covariates in data

mcmc

a list of various mcmc options

ODEopt

optional ODE solving options

distribution

one of c("normal","poisson","binomial")

seed

seed for random number generator

Details

Fit a generalized nonlinear mixed-effect model using the Stochastic Approximation Expectation-Maximization (SAEM) algorithm

Author(s)

Matthew Fidler & Wenping Wang


nlmixr documentation built on June 21, 2018, 5:04 p.m.