randomizeTau: Transformation of the observed time vector tau. Data...

In MMLR: Fitting Markov-Modulated Linear Regression Models

Description

Additional function to be used for simulation purposes (academical or research). Transforming of the observed time vector tau according to user preferences. Random disturbances are entered in the initial values of the vector tau. The expectation of new observed times coincides with initial values of vector tau.

Usage

randomizeTau(tau, p, k0 = 2, k1 = 1)

Arguments

tau	Vector (n x 1), n - number of observations
p	Scalar (from 1 to +inf), random number for simulation. The default value is 1
k0	Scalar (from 1 to +inf). Multiplicative parameter for transforming the initial value The default is k0 = 2.
k1	Scalar. The number of digits after the comma when rounded. The default is 1.

Details

Initial values of observation times are multiplied by a random value ($tau_i$ x k x rnd(0, 1)). All times are independent and time of ith observation has uniform distribution on (0, k$tau_i$).

Value

Vector with new observation times, according to user preferences.

Examples

tGiven <- matrix (c(6,4.8,1,2.6,6.4,1.7,2.9,4.4,1.5,3.4), nrow = 10, ncol = 1)
randomizeTau(tGiven,1,2,2)

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