Discrete Time Markov Chains with R
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The markovchain package aims to provide S4 classes and methods to easily handle Discrete Time Markov Chains (DTMCs), filling the gap with what is currently available in the CRAN repository.In this work, I provide an exhaustive description of the main functions included in the package, as well as hands-on examples.
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The markovchain package simulates time-independent and time-dependent Markov chains but is not designed to conduct economic evaluations.
“The markovchain package simulates time-independent, and time-dependent Markov chains but is not designed to conduct economic evaluations.”
From An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example (2023) · cites this paper as [10]
The Introduction describes simulating trajectories from a discrete-time Markov chain, and the Non homogeneous Markov chains section describes handling time-dependent chains; its example says rmarkovchain also works on those chains. The Additional information section says the package was designed for common operations on discrete-time Markov chains, but our copy does not explicitly establish that it is not designed to conduct economic evaluations. (LLM, conf=0.83)
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Research works printed but not linked: 15
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- Artur Araújo, Luís Meira-Machado, and Javier Roca-Pardiñas. TPmsm: Estimation of the transition probabilities in 3-state models. Journal of Statistical Software, 62(4):1-29, 2014. URL http://www. jstatsoft.org/v62/i04/.
- Brémaud, Pierre. Discrete-Time Markov Models. Springer-Verlag, 1999.
- Chambers, J.M. Software for Data Analysis: Programming with R. Statistics and computing. Springer- Verlag, 2008. ISBN 9780387759357.
- W.-K. Ching, M. K. Ng, and E. S. Fung. Higher-order multivariate markov chains and their applications. Linear Algebra and its Applications, 428(2):492-507, 2008.
- B. A. Craig and P. P. Sendi. Estimation of the transition matrix of a discrete-time markov chain. Health Economics, 11(1), 2002.
- Eddelbuettel, Dirk. Seamless R and C++ Integration with Rcpp. Springer-Verlag, New York, 2013. ISBN 978-1-4614-6867-7.
- Efron, B. Bootstrap methods: Another look at the jackknife. Ann. Statist., 7(1):1-26, 1979. URL http://dx.doi.org/10.1214/aos/1176344552. · DOI · Paper page
- C. H. Jackson. Multi-state models for panel data: The msm package for r. Journal of Statistical Software, 38(8):1-29, 2011. URL http://www.jstatsoft.org/v38/i08/.
- C. I. Jones. On the evolution of the world income distribution. Available at SSRN 59412, 1997.
- A. A. Markov. Issledovanie zamechatel nogo sluchaya zavisimyh ispytanij. Izvestiya Akademii Nauk, SPb, VI seriya, 1(93):61-80, 1907. [p84]
- Pablo J. Villacorta and José L. Verdegay. FuzzyStatProb: An r package for the estimation of fuzzy stationary probabilities from a sequence of observations of an unknown Markov chain. Journal of Statistical Software, 71(8):1-27, 2016. URL https://doi.org/10.18637/jss.v071.i08. · DOI
- M. Scholz. The R package clickstream: Analyzing clickstream data with markov chains. Journal of Statistical Software, 74(4):1-17, 2016. URL https://doi.org/10.18637/jss.v074.i04. · DOI
- W. J. Stewart. Introduction to the Numerical Solutions of Markov Chains. Princeton Univ. Press, 1994.
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Samara, J., Moossavi, S., Alshaikh, B., Ortega, V. A., Pettersen, V. K., Ferdous, T., Hoops, S. L., Soraisham, A., Vayalumkal, J., Dersch-Mills, D., et al. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.04.005 · Cited by 191 · see citing works
Alarid-Escudero, F., Krijkamp, E., Enns, E. A., Yang, A., Hunink, M. G. M., Pechlivanoglou, P., & Jalal, H. (2023) · Medical Decision Making · doi:10.1177/0272989x221103163 · Cited by 39 · see citing works
- Authors
- Spedicato, G.
- Corresponding author
- Spedicato, Giorgio,Alfredo
- Venue
- The R Journal
- Publisher
- The R Foundation
- Published
- 2017
- Volume
- 9
- Issue
- 2
- Pages
- 84
- ISSN
- 2073-4859 (ISSN-L)
- OpenAlex
- W2793759594
- Cited by
- 148
- References
- 0
- Citations by year
- 2026: 12 · 2025: 20 · 2024: 15 · 2023: 26 · 2022: 24 · 2021: 14 · 2020: 24 · 2019: 8 · 2018: 4 · 2017: 1
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- The R Journal (publishedVersion, cc-by)
- Lincoln (University of Nebraska) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Data Analysis with R
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Keywords
- discrete-time Markov chains, S4 classes, R package development
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