# Generate data from a dependent mixture model

### Description

`generate`

generates a dataset according to a
given `dmm`

.

### Usage

1 2 |

### Arguments

`ntimes` |
The number of repeated measurements, ie the length of the time series (this may be a vector containing the lengths of independent realiazations). |

`dmm` |
Object of class |

`nreal` |
The number of independent realizations that is to generated.
Each of them will have the dimension of |

### Details

`generate`

generates a date set of the specified dimensions
`ntimes`

and `nreal`

using the parameter values in
`dmm`

, which should be an object of class `dmm`

or
`mixdmm`

. `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.

### Value

Generate returns an object of class `markovdata`

. The
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
another attribute `incomp`

containing the components of each realization.

### Author(s)

Ingmar Visser i.visser@uva.nl

### See Also

`dmm`

, `markovdata`

### Examples

1 2 3 4 5 6 7 8 9 10 | ```
# 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)
``` |