markovchain_transition_classifier: Target Generator for Markov-chain Random Walk Simulation

In genpack/promer: This package will be a complete toolbox for process mining, management, prediction, simulation and optimization

Target Generator for Markov-chain Random Walk Simulation

Description

This function is a simple transition probability model based on memory-less markov-chain model. It randomly picks destination for each given transition respecting the probability distribution of each transition target. Transition probability distribution are extracted from given argument histobj. This is the default target generator engine for the transition system monte-carlo simulation. The TransitionSystem simulator engine calls this function multiple times during the sumulation.

Usage

markovchain_transition_classifier(histobj, input, ...)

Arguments

histobj	object of class TransitionSystem containing history of all transitions upto the current time current_time
input	dataframe containing transitions for which a transition end time needs to be generated
current_time	POSIXct containing the current time. All transition end times will be after the specified current time.

Value

dataframe with additional column nextStatus.

genpack/promer documentation built on Jan. 26, 2025, 11:30 p.m.