sim_path: Simulate the path of a time-inhomogeneous (semi-)Markov...

In AalenJohansen: Conditional Aalen-Johansen Estimation

Simulate the path of a time-inhomogeneous (semi-)Markov process until a maximal time

Description

Simulate the path of a time-inhomogeneous (semi-)Markov process until a maximal time

Usage

sim_path(i, rates, dists, t = 0, u = 0, tn = Inf, abs = numeric(0), bs = NA)

Arguments

i	The initial state, integer.
rates	The total transition rates out of states, a function with arguments state (integer), time (numeric), and duration (numeric) returning a rate (numeric).
dists	The distribution of marks, a function with arguments state (integer), time (numeric), and duration (numeric) returning a probability vector.
t	The initial time, numeric.
u	The initial duration (since the last transition), numeric. By default equal to zero
tn	The maximal time, numeric. By default equal to inifinity
abs	Vector indicating which states are absorbing. By default the last state is absorbing.
bs	Vector of upper bounds on the total transition rates. By default the bounds are determined using optimize, which might only identify a local maximum.

Value

A list concerning jump times and states, with the first time being the initial time t and state and the last time being tn (if not absorbed)

Examples

jump_rate <- function(i, t, u){if(i == 1){3*t} else if(i == 2){5*t} else{0}}
mark_dist <- function(i, s, v){if(i == 1){c(0, 1/3, 2/3)} else if(i == 2){c(1/5, 0, 4/5)} else{0}}
sim <- sim_path(sample(1:2, 1), t = 0, tn = 2, rates = jump_rate, dists = mark_dist)
sim

AalenJohansen documentation built on March 7, 2023, 6:43 p.m.