R: Simulate from a Parameterized MVN Mixture Model

simE {mclust} | R Documentation

## Simulate from a Parameterized MVN Mixture Model

### Description

Simulate data from a parameterized MVN mixture model.

### Usage

    simE(parameters, n, seed = NULL, ...)
    simV(parameters, n, seed = NULL, ...)
    simEII(parameters, n, seed = NULL, ...)
    simVII(parameters, n, seed = NULL, ...)
    simEEI(parameters, n, seed = NULL, ...)
    simVEI(parameters, n, seed = NULL, ...)
    simEVI(parameters, n, seed = NULL, ...)
    simVVI(parameters, n, seed = NULL, ...)
    simEEE(parameters, n, seed = NULL, ...)
    simVEE(parameters, n, seed = NULL, ...)
    simEVE(parameters, n, seed = NULL, ...)
    simVVE(parameters, n, seed = NULL, ...)
    simEEV(parameters, n, seed = NULL, ...)
    simVEV(parameters, n, seed = NULL, ...)
    simEVV(parameters, n, seed = NULL, ...)
    simVVV(parameters, n, seed = NULL, ...)

### Arguments

`parameters` | A list with the following components: `pro` A vector whose kth component is the mixing proportion for the kth component of the mixture model. If missing, equal proportions are assumed. `mean` The mean for each component. If there is more than one component, this is a matrix whose kth column is the mean of the kth component of the mixture model. `variance` A list of variance parameters for the model. The components of this list depend on the model specification. See the help file for `mclustVariance` for details.
`n` | An integer specifying the number of data points to be simulated.
`seed` | An optional integer argument to `set.seed()` for reproducible random class assignment. By default the current seed will be used. Reproducibility can also be achieved by calling `set.seed` before calling `sim`.
`...` | Catches unused arguments in indirect or list calls via `do.call`.

### Details

This function can be used with an indirect or list call using `do.call`, allowing the output of e.g. `mstep`, `em` `me`, `Mclust`, to be passed directly without the need to specify individual parameters as arguments.

### Value

A matrix in which first column is the classification and the remaining columns are the `n` observations simulated from the specified MVN mixture model.

`Attributes:` | `"modelName"` A character string indicating the variance model used for the simulation.

### See Also

`sim`, `Mclust`, `mstepE`, `mclustVariance`.

### Examples

    d <- 2
    G <- 2
    scale <- 1
    shape <- c(1, 9)

    O1 <- diag(2)
    O2 <- diag(2)[,c(2,1)]
    O <- array(cbind(O1,O2), c(2, 2, 2))
    O

    variance <- list(d= d, G = G, scale = scale, shape = shape, orientation = O)
    mu <- matrix(0, d, G) ## center at the origin
    simdat <- simEEV( n = 200,
                      parameters = list(pro=c(1,1),mean=mu,variance=variance),
                      seed = NULL)

    cl <- simdat[,1]

    sigma <- array(apply(O, 3, function(x,y) crossprod(x*y),
                     y = sqrt(scale*shape)), c(2,2,2))
    paramList <- list(mu = mu, sigma = sigma)
    coordProj( simdat, paramList = paramList, classification = cl)

[Package mclust version 5.4.9 Index]