These functions wrap multiple modular components into functional pipelines.
markov_ce_pipeline()
Markov Sampling, Simulation, and Cost Effectiveness Analysis Pipeline
markov_simulation_pipeline()
Markov Sampling and Simulation Pipeline
Functions (both R and Rcpp) that facilitate model sampling, simulation and analysis.
sample_markov()
Sample a Markov Model
sample_markov_base()
Sample a Markov Model Sample using Base R
simulate_markov()
Simulate a Markov Model Sample
simulate_markov_base()
Simulate a Markov Model Sample using Base R
ArmaSimulateMarkov()
Simulate a Markov Model Sample using RcppArmadillo
analyse_ce()
Analyse the Cost Effectiveness of Interventions
These functions (both R and Rcpp) are used internally by other functions to make simple operations modular.
markov_loop()
Inner Markov Loop in base R
ArmaMarkovLoop()
An inner Markov loop implemented using RcppArmadillo
Example reference models and their SpeedyMarkov implementations.
reference_two_state_markov()
Reference Two State Markov Model
example_two_state_markov()
Helper functions used in other package functions and to explore package functionality.
vector_arrange()
Arrange Vectorised Vector Samples
matrix_arrange()
Arrange Vectorised Matrix Samples
matrix_arrange_inner()
Arrange Vectorised Matrix Samples using R
MatrixArrange()
Arrange Vectorised Matrix Samples using Rcpp
calc_discounting()
Calculate Discounting Over the Model Run Time.
benchmark_markov()
Benchmarks Markov Model Simulation Approaches
Functions imported from other packages.
reexports
Objects exported from other packages