Package: mixAR 0.22.8.9000
Georgi N. Boshnakov
mixAR: Mixture Autoregressive Models
Model time series using mixture autoregressive (MAR) models. Implemented are frequentist (EM) and Bayesian methods for estimation, prediction and model evaluation. See Wong and Li (2002) <doi:10.1111/1467-9868.00222>, Boshnakov (2009) <doi:10.1016/j.spl.2009.04.009>), and the extensive references in the documentation.
Authors:
mixAR_0.22.8.9000.tar.gz
mixAR_0.22.8.9000.zip(r-4.5)mixAR_0.22.8.9000.zip(r-4.4)mixAR_0.22.8.9000.zip(r-4.3)
mixAR_0.22.8.9000.tgz(r-4.4-any)mixAR_0.22.8.9000.tgz(r-4.3-any)
mixAR_0.22.8.9000.tar.gz(r-4.5-noble)mixAR_0.22.8.9000.tar.gz(r-4.4-noble)
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mixAR.pdf |mixAR.html✨
mixAR/json (API)
NEWS
| # Install 'mixAR' in R: |
| install.packages('mixAR', repos = c('https://geobosh.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/geobosh/mixar/issues
Datasets:
- PortfolioData1 - Closing prices of four stocks
assymetricheteroskedasticitymixture-autoregressivestudent-ttime-series
Last updated 29 days agofrom:184019139b. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 25 2024 |
| R-4.5-win | OK | Oct 25 2024 |
| R-4.5-linux | OK | Oct 25 2024 |
| R-4.4-win | OK | Oct 25 2024 |
| R-4.4-mac | OK | Oct 25 2024 |
| R-4.3-win | OK | Oct 25 2024 |
| R-4.3-mac | OK | Oct 25 2024 |
Exports:%of%adjustLengthsb_showbayes_mixARBIC_compbx_dxChoose_pkcompanion_matrixcond_loglikcond_loglikSdist_normdistlisted_nparamed_parseed_skeletoned_srced_stdnormed_stdted_stdt0ed_stdt1em_est_distem_est_sigmaem_rinitem_tauem_tau_safeerrerr_kest_templetk2tauexampleModelsfdist_stdnormfdist_stdtfit_mixARfit_mixARregfit_mixVARfn_stdtft_stdtget_edistinitializeinnerisStablelabel_switchlastnlik_paramslik_params_boundsmake_fcond_likmarg_loglikmix_cdfmix_central_momentmix_ekmix_ekurtosismix_hatkmix_kurtosismix_locationmix_momentmix_ncompmix_pdfmix_qfmix_semix_variancemixAny_simmixARmixAR_BICmixAR_cond_probsmixAR_diagmixAR_permutemixAR_simmixAR_switchmixARemFixedPointmixARExperimentMixARGaussianmixARgenmixARgenemFixedPointmixARnoise_simmixARregmixFiltermixgenMstepmixMstepmixSARfitmixSubsolvemixVAR_simmixVARfitmultiStep_distnoise_distnoise_momentnoise_paramsnoise_randparam_score_stdtparametersparameters<-permn_colspermuteArparpredict_coefrag_modifyragged2charragged2vecraggedCoefraghat1randomArCoefficientsrandomMarParametersKernelrandomMarResidualsrow_lengthssampMuShiftsampSigmaTausampZpiset_noise_paramsshow_diffsimuExperimentstdnormabsmomentstdnormmomentstdtabsmomentstdtmomenttabsmomenttau2arcoeftau2probhattauCorrelatetauetk2sigmahattest_unswitchtomarparambyComptomarparambyTypetsDesignMatrixExtendedunswitch
Dependencies:BBclasscodacombinatcvare1071fastICAfBasicsfGarchgbutilsgsslatticeMASSMatrixMatrixModelsmcmcMCMCpackmvtnormpermuteproxyquadprogquantregrbibutilsRdpackSparseMspatialstabledistsurvivaltimeDatetimeSeries
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Mixture Autoregressive Models | mixAR-package |
| Bayesian sampling of mixture autoregressive models | bayes_mixAR |
| Choose the autoregressive order of MixAR components | Choose_pk |
| Log-likelihood of MixAR models | cond_loglik cond_loglikS |
| Functions for the standard normal distribution | dist_norm |
| Optimise scale parameters in MixARgen models | em_est_dist |
| Update the scale parameters of MixAR models | em_est_sigma tauetk2sigmahat |
| Gaussian EM-step with random initialisation | em_rinit etk2tau |
| Create estimation templates from MixAR model objects | est_templ |
| MixAR models for examples and testing | exampleModels moT_A moT_B moT_B2 moT_B3 moT_C1 moT_C2 moT_C3 moWL moWLar moWLgen moWLprob moWLsigma moWLt3v moWLtf moWL_A moWL_B moWL_I moWL_II |
| Fit mixture autoregressive models | fit_mixAR fit_mixAR,ANY,ANY,ANY-method fit_mixAR,ANY,MixAR,list-method fit_mixAR,ANY,MixAR,missing-method fit_mixAR,ANY,MixAR,MixAR-method fit_mixAR,ANY,MixAR,numeric-method fit_mixAR,ANY,MixARGaussian,MixAR-method fit_mixAR,ANY,numeric,missing-method fit_mixAR,ANY,numeric,numeric-method fit_mixAR-methods |
| Fit time series regression models with mixture autoregressive residuals | fit_mixARreg fit_mixARreg,ANY,ANY,missing,list-method fit_mixARreg,ANY,ANY,MixAR,list-method fit_mixARreg,ANY,data.frame,missing,list-method fit_mixARreg,ANY,data.frame,MixAR,missing-method fit_mixARreg,ANY,matrix,missing,list-method fit_mixARreg,ANY,matrix,MixAR,missing-method fit_mixARreg,ANY,numeric,missing,list-method fit_mixARreg,ANY,numeric,MixAR,missing-method fit_mixARreg-methods mixARreg |
| Fit mixture vector autoregressive models | fit_mixVAR fit_mixVAR,ANY,ANY-method fit_mixVAR,ANY,MixVAR-method fit_mixVAR-methods |
| Generator functions for noise distributions | b_show distlist ed_nparam ed_parse ed_skeleton ed_src ed_stdnorm ed_stdt ed_stdt0 ed_stdt1 fdist_stdnorm fdist_stdt fnoise fn_stdt ft_stdt |
| Methods for function 'get_edist' in package 'mixAR' | get_edist,MixAR-method get_edist,MixARGaussian-method get_edist,MixARgen-method get_edist-methods |
| Generalised inner product and methods for class '"MixComp"' | inner inner,ANY,ANY,ANY,ANY-method inner,MixComp,missing,missing,missing-method inner,MixComp,numeric,ANY,ANY-method inner,MixComp,numeric,ANY,missing-method inner,MixComp,numeric,missing,missing-method inner,numeric,MixComp,missing,missing-method inner-methods |
| Check if a MixAR model is stable | isStable |
| A posteriori relabelling of a Markov chain | label_switch |
| Vector of parameters of a MixAR model | lik_params lik_params,MixAR-method lik_params,MixARgen-method lik_params-methods |
| Create a function for computation of conditional likelihood | make_fcond_lik make_fcond_lik,MixAR,numeric-method make_fcond_lik-methods |
| Calculate marginal loglikelihood at high density points of a MAR model. | marg_loglik |
| Function and methods to compute component residuals for MixAR models | mix_ek mix_ek,MixAR,numeric,missing,numeric,logical-method mix_ek,MixAR,numeric,missing,numeric,missing-method mix_ek,MixAR,numeric,numeric,missing,logical-method mix_ek,MixAR,numeric,numeric,missing,missing-method mix_ek-methods |
| Compute component predictions for MixAR models | mix_hatk mix_hatk,MixAR,numeric,numeric,missing-method mix_hatk-methods |
| Conditional moments of MixAR models | mix_central_moment mix_ekurtosis mix_kurtosis mix_location mix_moment mix_variance |
| Number of rows or columns of a MixComp object | mix_ncomp mix_ncomp,MixAR-method mix_ncomp,MixComp-method mix_ncomp-methods |
| Conditional pdf's and cdf's of MixAR models | mix_cdf mix_cdf,MixARGaussian,missing,missing,numeric-method mix_cdf,MixARGaussian,numeric,missing,numeric-method mix_cdf,MixARGaussian,numeric,numeric,missing-method mix_cdf,MixARgen,missing,missing,numeric-method mix_cdf,MixARgen,numeric,missing,numeric-method mix_cdf,MixARgen,numeric,numeric,missing-method mix_cdf-methods mix_pdf mix_pdf,MixARGaussian,missing,missing,numeric-method mix_pdf,MixARGaussian,numeric,missing,numeric-method mix_pdf,MixARGaussian,numeric,numeric,missing-method mix_pdf,MixARgen,missing,missing,numeric-method mix_pdf,MixARgen,numeric,missing,numeric-method mix_pdf,MixARgen,numeric,numeric,missing-method mix_pdf-methods |
| Conditional quantile functions of MixAR models | mix_qf mix_qf,MixARGaussian,missing,missing,missing,numeric-method mix_qf,MixARGaussian,numeric,missing,missing,numeric-method mix_qf,MixARGaussian,numeric,numeric,numeric,missing-method mix_qf-methods |
| Compute standard errors of estimates of MixAR models | mix_se mix_se,ANY,list-method mix_se,ANY,MixAR-method mix_se,ANY,MixARGaussian-method mix_se-methods |
| BIC based model selection for MixAR models | BIC_comp mixAR_BIC |
| The E-step of the EM algorithm for MixAR models | mixAR_cond_probs |
| Diagnostic checks for mixture autoregressive models | mixAR_diag tsdiag tsdiag.MixAR |
| Simulate from MixAR models | mixAny_sim mixAR_sim |
| Relabel the components of a MixAR model | mixAR_permute mixAR_switch |
| Class '"MixAR"' - mixture autoregressive models | MixAR-class |
| Create MixAR objects | mixAR mixAR,ANY-method mixAR,MixAR-method mixAR-methods |
| EM estimation for mixture autoregressive models | mixARemFixedPoint mixARgenemFixedPoint |
| mixAR models with Gaussian noise components | MixARGaussian MixARGaussian-class |
| Class '"MixARgen"' | mixARgen MixARgen-class |
| Simulate white noise series from a list of functions and vector of regimes | mixARnoise_sim |
| Class '"MixComp"' - manipulation of MixAR time series | *,character,MixComp-method *,function,MixComp-method *,MixComp,MixComp-method *,MixComp,numeric-method *,numeric,MixComp-method +,MixComp,numeric-method +,numeric,MixComp-method -,MixComp,missing-method -,MixComp,numeric-method -,numeric,MixComp-method /,MixComp,numeric-method /,numeric,MixComp-method dim,MixComp-method MixComp-class ^,MixComp,numeric-method |
| Filter time series with MixAR filters | mixFilter mixFilter,ANY,ANY,ANY-method mixFilter,numeric,raggedCoef,numeric-method mixFilter-methods |
| M-step for models from class MixARgen | mixgenMstep |
| Internal functions for estimation of MixAR models with Gaussian components | mixMstep tau2arcoef tauCorrelate |
| Fit mixture autoregressive models with seasonal AR parameters | mixSARfit |
| Simulate from multivariate MixAR models | mixVAR_sim |
| Class '"MixVAR"' - mixture vector autoregressive models | MixVAR-class |
| Fit mixture vector autoregressive models | mixVARfit |
| MixVAR models with multivariate Gaussian noise components | MixVARGaussian MixVARGaussian-class |
| Multi-step predictions for MixAR models | multiStep_dist multiStep_dist,MixAR,numeric,numeric,numeric-method multiStep_dist,MixARGaussian,numeric,missing,ANY-method multiStep_dist,MixARGaussian,numeric,missing,missing-method multiStep_dist-methods |
| Internal mixAR functions | get_edist noise_dist noise_params noise_rand set_noise_params |
| Methods for function 'noise_dist' in package 'mixAR' | noise_dist,MixAR-method noise_dist,MixARGaussian-method noise_dist,MixARgen-method noise_dist-methods |
| Methods for function 'noise_params' in package 'mixAR' | noise_params,MixAR-method noise_params,MixARgen-method noise_params-methods |
| Methods for function 'noise_rand' in package 'mixAR' | noise_rand,MixAR-method noise_rand,MixARGaussian-method noise_rand,MixARgen-method noise_rand-methods |
| Set or extract the parameters of MixAR objects | parameters parameters,ANY-method parameters,MixAR-method parameters-methods parameters<- parameters<-,ANY-method parameters<-,MixAR-method parameters<--methods set_parameters set_parameters,ANY-method set_parameters,MixAR-method set_parameters-methods |
| Infix operator to apply functions to matrix-like objects | %of% %of%,ANY,ANY-method %of%,character,MixComp-method %of%,function,MixComp-method %of%,list,MixComp-method %of%-methods percent_of |
| All permutations of the columns of a matrix | permn_cols |
| Closing prices of four stocks | PortfolioData1 |
| Exact predictive parameters for multi-step MixAR prediction | predict_coef |
| Small utilities for ragged objects | ragged2vec rag_modify |
| Class '"raggedCoef"' - ragged list objects | anyNA,raggedCoef-method dim,raggedCoef-method length,raggedCoef-method raggedCoef raggedCoef-class [,raggedCoef,missing,missing,ANY-method [,raggedCoef,missing,numeric,ANY-method [,raggedCoef,numeric,missing,ANY-method [,raggedCoef,numeric,numeric,ANY-method [-methods [<-,raggedCoef,ANY,ANY,numeric-method [<-,raggedCoef,ANY,missing,list-method [<-,raggedCoef,ANY,missing,matrix-method [<-,raggedCoef,ANY,missing,numeric-method [<-,raggedCoef,missing,missing,ANY-method [<-,raggedCoef,missing,missing,list-method [<-,raggedCoef,missing,missing,matrix-method [<-,raggedCoef,missing,missing,numeric-method [<-,raggedCoef,numeric,missing,ANY-method [<-,raggedCoef,numeric,numeric,ANY-method [[,raggedCoef,ANY,ANY-method [[,raggedCoef,ANY,missing-method [[-methods [[<-,raggedCoef,ANY,ANY,numeric-method [[<-,raggedCoef,ANY,missing,numeric-method [[<--methods |
| Class '"raggedCoefS"' - ragged list | raggedCoefS raggedCoefS-class [,raggedCoefS,missing,missing,ANY-method [,raggedCoefS,missing,numeric,ANY-method [,raggedCoefS,numeric,missing,ANY-method [,raggedCoefS,numeric,numeric,ANY-method [[,raggedCoefS,ANY,ANY-method [[,raggedCoefS,ANY,missing-method [[<-,raggedCoefS,ANY,ANY,numeric-method [[<-,raggedCoefS,ANY,missing,list-method |
| Class '"raggedCoefV"' - ragged list | raggedCoefV raggedCoefV-class [,raggedCoefV,missing,ANY,ANY-method [,raggedCoefV,missing,numeric,ANY-method [,raggedCoefV,numeric,ANY,ANY-method [,raggedCoefV,numeric,ANY-method [,raggedCoefV,numeric,missing,ANY-method [,raggedCoefV,numeric,numeric,ANY-method [[,raggedCoefV,missing,ANY-method [[,raggedCoefV,numeric,ANY-method |
| Filter a time series with options to shift and scale | raghat1 |
| Random initial values for MixAR estimation | randomArCoefficients randomMarParametersKernel randomMarResiduals tsDesignMatrixExtended |
| Methods for function 'row_lengths' in package 'mixAR' | row_lengths row_lengths,ANY-method row_lengths,MixAR-method row_lengths,raggedCoef-method row_lengths-methods |
| Sampling functions for Bayesian analysis of mixture autoregressive models | sampMuShift sampSigmaTau sampZpi |
| Show differences between two models | show_diff show_diff,MixAR,MixAR-method show_diff,MixARGaussian,MixARgen-method show_diff,MixARgen,MixARGaussian-method show_diff,MixARgen,MixARgen-method show_diff-methods |
| Perform simulation experiments | simuExperiment |
| Compute moments and absolute moments of standardised-t and normal distributions | stdnormabsmoment stdnormmoment stdtabsmoment stdtmoment tabsmoment |
| Translations of my old MixAR Mathematica functions | permuteArpar tomarparambyComp tomarparambyType |