LMest (version 3.0.0)

drawLMbasiccont: Draw samples from the basic LM model for continuous outcomes

Description

Function that draws samples from the basic LM model for continuous outcomes with specific parameters.

Usage

drawLMbasiccont(piv, Pi, Mu, Si, n, est = NULL,
                format = c("long","matrices"), seed = NULL)

Arguments

piv

vector of initial probabilities of the latent Markov chain

Pi

set of transition probabilities matrices (k x k x TT)

Mu

matrix of conditional means for the response variables (r x k)

Si

var-cov matrix common to all states (r x r)

n

sample size

est

object of class LMbasiccont (LMbasiccont-class)

format

character string indicating the format of final responses matrix

seed

an integer value with the random number generator state

Value

Y

array of continuous outcomes (n x TT x r)

piv

vector of initial probabilities of the latent Markov chain

Pi

set of transition probabilities matrices (k x k x TT)

Mu

matrix of conditional means for the response variables (r x k)

Si

var-cov matrix common to all states (r x r)

n

sample size

est

object of class LMbasiccont (LMbasiccont-class)

Examples

# NOT RUN {
# draw a sample for 1000 units and 3 response variable
n <- 1000
TT <- 5
k <- 2
r <- 3 #number of response variables

piv <- c(0.7,0.3)
Pi <- matrix(c(0.9,0.1,0.1,0.9), k, k)
Pi <- array(Pi, c(k, k, TT))
Pi[,,1] <- 0
Mu <- matrix(c(-2,-2,0,0,2,2), r, k)
Si <- diag(r)
out <- drawLMbasiccont(piv, Pi, Mu, Si, n)


require(mmm)
data(multiLongGaussian)

t <- rep(1:4, times = max(multiLongGaussian$ID))
multiLongGaussian <- data.frame(t = t, multiLongGaussian)

est <- lmestCont(responsesFormula = resp1 + resp2 ~ NULL,
                 index = c("ID", "t"),
                 data = multiLongGaussian,
                 k = 3,
                 modBasic = 1,
                 tol = 10^-5)

out2 <- drawLMbasiccont(est = est, n = 100, format = "long", seed = 4321)

# }
# NOT RUN {

# }