randomizeX: Transformation of regressors' matrix X. Data preparation...

In MMLR: Fitting Markov-Modulated Linear Regression Models

Description

Additional function to be used for simulation purposes (academical or research). Transforming the matrix of regressors according to user preferences. Random disturbances (according to a chosen distribution) are entered in the initial values of the matrix X. The expectation of the resulting matrix coincides with the initial matrix X.

Usage

randomizeX(X, p = 1, k0 = 1, k1 = 0.5, k2 = 1, k3 = 1)

Arguments

X	Matrix (n x k), n - number of observations, k - number of columns (k - 1 - number of regressors). Note, that 1st column contains only ones (1) (intercept)
p	Scalar (from 1 to +inf), random number for simulation. The default value is 1
k0	Scalar. Number from 1 to 3 (distribution selection). k0 = 1 - uniform distribution (RV Z ~ U (K1, k2)). k0 = 2 - exponential distribution (RV Z ~ exp(lambda)). k0 = 3 - Gamma distribution (RV Z ~ gamma(shape, rate)). The default value is k0 = 1.
k1	Scalar. 1) If k0 = 1, then k1 is a left boundary of uniform distribution (RV Z ~ U(k1, k2)). 2) If k0 = 2, then k1 is a parameter lambda of exponential distribution (RV Z ~ exp(lambda)). 3) If k0 = 3, then k1 is a shape parameter of Gamma distribution (RV Z ~ gamma(shape, rate)). The default is k1 = 0.5.
k2	Scalar. 1) If k0 = 1, then k2 is a right boundary of uniform distribution (RV Z ~ U(k1, k2). 2) If k0 = 3, then k2 is a rate parameter of Gamma distribution (RV Z ~ gamma(shape, rate)). The default is k2 = 1.
k3	Scalar. The number of digits after the comma when rounded. The default value is 1.

Details

Random perturbations are added to the initial values of matrix X elements ($X_i,j$ + rnd), which are distributed according to a chosen distribution (possible alternatives: uniform, exponential and gamma distribution).

Value

New transformed matrix of regressors (n x k), according to user preferences.

Examples

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))
randomizeX(Xtest,1,1,1,2,2)

MMLR documentation built on Jan. 9, 2020, 5:06 p.m.