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NHMSAR  

Non-Homogeneous Markov Switching Autoregressive Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("NHMSAR", "1.19")



Attach the package and use:
library("NHMSAR")
Maintained by
Valerie Monbet
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-11-23
Latest Update: 2022-02-09
Description:
Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations. Penalization methods are implemented for Markov Switching Vector Autoregressive Models of order 1 only. Most functions of the package handle missing values.
How to cite:
Valerie Monbet (2014). NHMSAR: Non-Homogeneous Markov Switching Autoregressive Models. R package version 1.19, https://cran.r-project.org/web/packages/NHMSAR
Previous versions and publish date:
1.0 (2014-11-23 23:32), 1.1 (2015-06-09 17:12), 1.4 (2016-04-24 16:51), 1.5 (2017-05-25 19:01), 1.6 (2017-08-31 10:11), 1.7 (2017-12-05 07:07), 1.9 (2018-07-22 11:30), 1.10 (2018-07-24 23:30), 1.11 (2018-08-06 09:50), 1.12 (2018-09-23 15:00), 1.14 (2019-10-28 13:20), 1.15 (2019-11-22 09:50), 1.16 (2020-03-14 09:50), 1.17 (2020-04-07 19:20), 1.19 (2022-02-09 08:40)
Other packages that cited NHMSAR R package
View NHMSAR citation profile
Other R packages that NHMSAR depends, imports, suggests or enhances
Functions, R codes and Examples using the NHMSAR R package
Some associated functions: Cond.prob.MSAR . ENu_graph . Estep.MSAR.VM . Estep.MSAR . MeanDurOver . MeanDurUnder . Mstep.classif . Mstep.hh.MSAR.VM . Mstep.hh.MSAR . Mstep.hh.MSAR.with.constraints . Mstep.hh.SCAD.MSAR . Mstep.hh.SCAD.cw.MSAR . Mstep.hh.lasso.MSAR . Mstep.hh.reduct.MSAR . Mstep.hh.ridge.MSAR . Mstep.hn.MSAR . Mstep.nh.MSAR.VM . Mstep.nh.MSAR . Mstep.nn.MSAR . NH-MSAR-package . PibDetteDemoc . Wind . WindDir . cor.MSAR . cross.cor.MSAR . emisprob.MSAR.VM . fit.MSAR.VM . fit.MSAR . forecast.prob.MSAR . forwards_backwards . init.theta.MSAR.VM . init.theta.MSAR . log_dens_Von_Mises . meteo.data . nhforwards_backwards . prediction.MSAR . regimes.plot.MSAR . simule.nh.MSAR.VM . simule.nh.MSAR . simule_MC . test.model.MSAR . test.model.vect.MSAR . valid_all.MSAR . viterbi_path . 
Some associated R codes: EM_converged.R . ENu_graph.R . Estep.MSAR.R . Estep.MSAR.VM.R . MeanDurOver.R . MeanDurUnder.R . Mstep.classif.R . Mstep.hh.MSAR.R . Mstep.hh.MSAR.VM.R . Mstep.hh.MSAR.with.constraints.R . Mstep.hh.SCAD.MSAR.R . Mstep.hh.SCAD.cw.MSAR.R . Mstep.hh.lasso.MSAR.R . Mstep.hh.reduct.MSAR.R . Mstep.hh.ridge.MSAR.R . Mstep.hn.MSAR.R . Mstep.nh.ARfix.MSAR.R . Mstep.nh.MSAR.R . Mstep.nh.MSAR.VM.R . Mstep.nn.MSAR.R . NH-MSAR-VM-internal.R . NH-MSAR-internal.R . as.thetaMSAR.R . as.thetaMSAR.VM.R . cor.MSAR.R . cross.cor.MSAR.R . cross.cor1.MSAR.R . deplie.VM.R . deplie.c.VM.R . deplie2.R . deplie2.VM.R . dim.thetaMSAR.R . emis4ps.MSAR.R . emisprob.MSAR.R . emisprob.MSAR.VM.R . fit.MSAR.R . fit.MSAR.VM.R . forecast.prob.MSAR.R . forwards_backwards.R . init.theta.MSAR.R . init.theta.MSAR.VM.R . init.theta.MSAR.miss.R . is.thetaMSAR.R . ll_gauss.MSAR.R . ll_gausshn.MSAR.R . ll_gausshn_p0.MSAR.R . ll_vonMises.MSAR.R . ll_vonMises.c.MSAR.R . log_dens_Von_Mises.R . loglik_nh_inp.R . loglik_nh_inp.VM.R . mk_stochastic.R . nhforwards_backwards.R . normalise.R . para_trans.R . para_trans_inv.R . pdf.norm.R . plie.VM.R . plie.c.VM.R . plie2.R . plie2.VM.R . prediction.MSAR.R . prediction.h_steps_ahead.MSAR.R . print.thetaMSAR.R . print.thetaMSAR.VM.R . reg_scad.R . regimes.plot.MSAR.R . repmat.R . sample.VM.R . simule.nh.MSAR.R . simule.nh.MSAR.VM.R . simule_MC.R . test.model.MSAR.R . test.model.vect.MSAR.R . tps_sejour.R . tps_sejour_sup.R . valid_all.MSAR.R . viterbi_path.R .  Full NHMSAR package functions and examples
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