simulate_nlme: Simulate samples from a nonlinear mixed model from fixed...

In nlraa: Nonlinear Regression for Agricultural Applications

Simulate samples from a nonlinear mixed model from fixed effects

Description

Simulate multiple samples from a nonlinear model

Usage

simulate_nlme(
  object,
  nsim = 1,
  psim = 1,
  value = c("matrix", "data.frame"),
  data = NULL,
  ...
)

Arguments

object	object of class gnls or nlme
nsim	number of samples, default 1
psim	simulation level for fixed and random parameters see simulate_nlme_one for more details.
value	whether to return a matrix (default) or an augmented data frame
data	the data argument is needed when using this function inside user defined functions.
...	additional arguments to be passed to either simulate_gnls or simulate_nlme_one

Details

The details can be found in either simulate_gnls or simulate_nlme_one. This function is very simple and it only sets up a matrix and a loop in order to simulate several instances of model outputs.

Value

It returns a matrix with simulated values from the original object with number of rows equal to the number of rows of fitted and number of columns equal to the number of simulated samples (‘nsim’). In the case of ‘data.frame’ it returns an augmented data.frame, which can potentially be a very large object, but which makes furhter plotting more convenient.

Examples

require(nlme)
data(barley, package = "nlraa")
barley2 <- subset(barley, year < 1974)
fit.lp.gnls2 <- gnls(yield ~ SSlinp(NF, a, b, xs), data = barley2)
barley2$year.f <- as.factor(barley2$year)
cfs <- coef(fit.lp.gnls2)
fit.lp.gnls3 <- update(fit.lp.gnls2, 
                      params = list(a + b + xs ~ year.f),
                      start = c(cfs[1], 0, 0, 0, 
                                cfs[2], 0, 0, 0,
                                cfs[3], 0, 0, 0))
                                
sims <- simulate_nlme(fit.lp.gnls3, nsim = 3)

nlraa documentation built on July 9, 2023, 6:08 p.m.