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hhsmm  

Hidden Hybrid Markov/Semi-Markov Model Fitting
View on CRAN: Click here


Download and install hhsmm package within the R console
Install from CRAN:
install.packages("hhsmm")

Install from Github:
library("remotes")
install_github("cran/hhsmm")

Install by package version:
library("remotes")
install_version("hhsmm", "0.4.2")



Attach the package and use:
library("hhsmm")
Maintained by
Morteza Amini
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-31
Latest Update: 2023-08-08
Description:
Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) , which also includes several tools for handling missing data, nonparametric mixture of B-splines emissions (Langrock et al., 2015 ), fitting regime switching regression (Kim et al., 2008 ) and auto-regressive hidden hybrid Markov/semi-Markov model, spline-based nonparametric estimation of additive state-switching models (Langrock et al., 2018 ) and many other useful tools (read for more description: Amini et al., 2022 and its arxiv version: ).
How to cite:
Morteza Amini (2021). hhsmm: Hidden Hybrid Markov/Semi-Markov Model Fitting. R package version 0.4.2, https://cran.r-project.org/web/packages/hhsmm. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.2 (2021-06-16 09:10), 0.1.3 (2021-09-13 07:50), 0.1 (2021-05-31 12:10), 0.2.0 (2021-10-13 11:30), 0.2.1 (2021-10-18 10:20), 0.2.2 (2021-11-23 11:10), 0.2.3 (2021-12-01 13:00), 0.2.4 (2022-01-10 08:52), 0.2.5 (2022-02-08 11:40), 0.3.1 (2022-02-28 10:30), 0.3.2 (2022-05-29 07:30), 0.3.3 (2022-08-05 16:50), 0.3.4 (2023-01-07 08:10), 0.3.5 (2023-03-06 09:30), 0.3.6 (2023-08-08 10:10), 0.3.7 (2024-05-01 09:30), 0.4.0 (2024-05-08 15:40), 0.4.1 (2024-09-03 07:40)
Other packages that cited hhsmm R package
View hhsmm citation profile
Other R packages that hhsmm depends, imports, suggests or enhances
Complete documentation for hhsmm
Functions, R codes and Examples using the hhsmm R package
Some associated functions: additive_reg_mstep . addreg_hhsmm_predict . cov.miss.mix.wt . cov.mix.wt . dmixlm . dmixmvnorm . dmultinomial.hhsmm . dnonpar . dnorm_additive_reg . hhsmmdata . hhsmmfit . hhsmmspec . homogeneity . initial_cluster . initial_estimate . initialize_model . lagdata . ltr_clus . ltr_reg_clus . make_model . miss_mixmvnorm_mstep . mixdiagmvnorm_mstep . mixlm_mstep . mixmvnorm_mstep . mstep.multinomial . nonpar_mstep . predict.hhsmm . predict.hhsmmspec . raddreg . rmixar . rmixlm . rmixmvnorm . rmultinomial.hhsmm . score . simulate.hhsmmspec . train_test_split . 
Some associated R codes: add-states.R . additive-reg-mstep.R . addpred.R . build_d.R . check-hhsmmspec.R . cov-miss-mix-wt.R . cov-mix-wt.R . densComputeMiss.R . dfcalc.R . discret-check.R . dlog.R . dmixlm.R . dmultinomial-hhsmm.R . dmvnorm-mix-hhsmm.R . dnbinom-hhsmm.R . dnonpar.R . dnorm-additive-reg.R . dpois-hhsmm.R . fitnbinom.R . gammafit.R . hhsmmdata.R . hhsmmfit.R . hhsmmspec.R . homogeneity.R . initial-cluster.R . initial-estimate.R . initialize-model.R . kreg.R . lagdata.R . lnormfit.R . logdistfit.R . ltr-clus.R . ltr-clus2.R . ltr_reg_clus.R . ltr_reg_clus2.R . make-model.R . mix-weights-calc.R . mixdiagmvnorm_mstep.R . mstep-missing-mix-mvnorm.R . mstep-mix-lm.R . mstep-mix-mvnorm.R . mstep-multinomial.R . nonpar_mstep.R . plog.R . plot-hhsmm-data.R . plot-hhsmm.R . predict-hhsmm.R . predict-hhsmmspec.R . print-hhsmmspec.R . raddreg.R . rbinom-hhsmm.R . rlog.R . rmixar.R . rmixlm.R . rmultinomial-hhsmm.R . rmvnorm-mix-hhsmm.R . rpois-hhsmm.R . score.R . simulate-hhsmm.R . simulate_markov.R . summary-hhsmm.R . symetric.R . train-test-split.R . update-sojourn.R . weibullfit.R .  Full hhsmm package functions and examples
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