Generate data from a dependent mixture model
generate generates a dataset according to a
The number of repeated measurements, ie the length of the time series (this may be a vector containing the lengths of independent realiazations).
Object of class
The number of independent realizations that is to generated.
Each of them will have the dimension of
generate generates a date set of the specified dimensions
nreal using the parameter values in
dmm, which should be an object of class
generate does not handle multi group models,
which can be run separately.
This function is used in the
bootstrap'ping routine to compute
standard errors based on parametric bootstraps.
Generate returns an object of class
return object has an attribute called instates, a vector with the starting
states of each realization. When the model is a mixture the return has
incomp containing the components of each realization.
Ingmar Visser email@example.com
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# create a 2 state model with one continuous and one binary response # with start values provided in st st <- c(1,0.9,0.1,0.2,0.8,2,1,0.7,0.3,5,2,0.2,0.8,0.5,0.5) mod <- dmm(nsta=2,itemt=c(1,2), stval=st) # generate two series of lengths 100 and 50 respectively using above model gen<-generate(c(100,50),mod) summary(gen) plot(gen)
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