MMLR (version 0.2.0)

randomizeInitState: Transformation of vector with initial states I for various observations. Data preparation stage for simulation.

Description

Additional function to be used for simulation purposes (academical or research). Transforming of vector with initial states I for various observations with respect to stationary distribution of the states for the random environment.

Usage

randomizeInitState(StatPr, X, p = 1)

Arguments

StatPr

Vector (m x 1), m - number of states, m = 2,3,.. .The vector with stationary probabilities, user-defined vector.

X

Matrix (n x k), n - number of observations, k - number of columns (k - 1 - number of regressors). The matrix is needed to get the number of observations.

p

Scalar (from 1 to +inf), random number for simulation. The default value is 1.

Value

Vector with new initial states, according to stationary distribution of the states for the random environment.

Details

The initial states (m - number of states, m = 2,3,...) for various observations are independent and are chosen with respect to stationary distribution of the states for the random environment. The vector with stationary probabilities is user-defined vector.

Examples

# NOT RUN {
Xtest <- cbind(rep_len(1,10),c(2,5,7,3,1,1,2,2,3,6), c(5,9,1,2,3,2,3,5,2,2))
StatPr <- matrix (c(0.364,0.242,0.394), nrow = 3, ncol = 1)
randomizeInitState(StatPr,Xtest,1)
# }