Package: uGMAR 3.6.1

uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models

Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR), Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Mika Meitz, Daniel Preve, Pentti Saikkonen (2023) <doi:10.1080/03610926.2021.1916531>, Savi Virolainen (2022) <doi:10.1515/snde-2020-0060>.

Authors:Savi Virolainen [aut, cre]

uGMAR_3.6.1.tar.gz
uGMAR_3.6.1.zip(r-4.7)uGMAR_3.6.1.zip(r-4.6)uGMAR_3.6.1.zip(r-4.5)
uGMAR_3.6.1.tgz(r-4.6-any)uGMAR_3.6.1.tgz(r-4.5-any)
uGMAR_3.6.1.tar.gz(r-4.7-any)uGMAR_3.6.1.tar.gz(r-4.6-any)
uGMAR_3.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
uGMAR/json (API)
NEWS

# Install 'uGMAR' in R:
install.packages('uGMAR', repos = c('https://saviviro.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/saviviro/ugmar/issues

Datasets:
  • M10Y1Y - Spread between 10-Year and 1-Year Treasury rates: M10Y1Y
  • simudata - Simulated data
  • T10Y1Y - Spread between 10-Year and 1-Year Treasury rates: T10Y1Y
  • TBFF - Spread between the 3-month Treasury bill rate and the effective federal funds rate: TBFF

On CRAN:

Conda:

4.72 score 1 stars 52 scripts 307 downloads 34 exports 5 dependencies

Last updated from:f583fd69dc. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK151
source / vignettesOK202
linux-release-x86_64OK152
macos-release-arm64OK157
macos-oldrel-arm64OK127
windows-develOK107
windows-releaseOK96
windows-oldrelOK97
wasm-releaseOK113

Exports:add_dataalt_gsmarcalc_gradientcalc_hessiancond_moment_plotcond_momentsdiagnostic_plotfitGSMARGAfitget_ar_rootsget_focget_gradientget_hessianget_regime_autocovsget_regime_meansget_regime_varsget_socGSMARis_stationaryiterate_moreloglikelihoodLR_testmixing_weightsprofile_logliksquantile_residual_plotquantile_residual_testsquantile_residualsrandom_indsmart_indstmar_to_gstmarstmarpars_to_gstmarswap_parametrizationuncond_momentsWald_test

Dependencies:BrobdingnaggsllatticeMatrixpbapply

uGMAR: A Family of Mixture Autoregressive Models in R

Rendered fromuGMARpaper.Rnwusingutils::Sweaveon Jun 01 2026.

Last update: 2025-10-06
Started: 2021-05-05

Readme and manuals

Help Manual

Help pageTopics
uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive ModelsuGMAR-package uGMAR
Add data to object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR modeladd_data
Construct a GSMAR model based on results from an arbitrary estimation round of 'fitGSMAR'alt_gsmar
Calculate gradient or Hessian matrixcalc_gradient calc_hessian get_foc get_gradient get_hessian get_soc
Conditional mean or variance plot for GMAR, StMAR, and G-StMAR modelscond_moment_plot
Calculate conditional moments of GMAR, StMAR, or G-StMAR modelcond_moments
Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR modelsdiagnostic_plot
Estimate Gaussian or Student's t Mixture Autoregressive modelfitGSMAR
Genetic algorithm for preliminary estimation of GMAR, StMAR, or G-StMAR modelGAfit
Calculate absolute values of the roots of the AR characteristic polynomialsget_ar_roots
Calculate regime specific autocovariances *gamma*_{m,p}get_regime_autocovs
Calculate regime specific means mu_{m}get_regime_means
Calculate regime specific variances gamma_{m,0}get_regime_vars
Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR modelGSMAR logLik.gsmar plot.gsmar print.gsmar residuals.gsmar summary.gsmar
Check the stationary condition of specified GMAR, StMAR, or G-StMAR model.is_stationary
Maximum likelihood estimation of GMAR, StMAR, or G-StMAR model with preliminary estimatesiterate_more
Compute the log-likelihood of GMAR, StMAR, or G-StMAR modelloglikelihood
Perform likelihood ratio testLR_test
Spread between 10-Year and 1-Year Treasury rates: M10Y1YM10Y1Y
Calculate mixing weights of GMAR, StMAR or G-StMAR modelmixing_weights
Pick phi_0 (or mu), AR-coefficients, and variance parameters from a parameter vectorpick_pars
Plot method for class 'gsmarpred' objectsplot.gsmarpred
Quantile residual tests for GMAR, StMAR , and G-StMAR modelsplot.qrtest print.qrtest quantile_residual_tests
Forecast GMAR, StMAR, or G-StMAR processpredict.gsmar
Print method for class 'gsmarpred' objectsprint.gsmarpred
Print method from objects of class 'gsmarsum'print.gsmarsum
Plot profile log-likelihoods around the estimatesprofile_logliks
Plot quantile residual time series and histogramquantile_residual_plot
Compute quantile residuals of GMAR, StMAR, or G-StMAR modelquantile_residuals
Create random GMAR, StMAR, or G-StMAR model compatible parameter vectorrandom_ind smart_ind
Reform any parameter vector into standard form.reform_parameters
Simulated datasimudata
Simulate obsercations from GMAR, StMAR, and G-StMAR processessimulate.gsmar
Estimate a G-StMAR model based on a StMAR model with large degrees of freedom parametersstmar_to_gstmar
Transform a StMAR or G-StMAR model parameter vector to a corresponding G-StMAR model parameter vector with large dfs parameters reduced.stmarpars_to_gstmar
Swap the parametrization of object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR modelswap_parametrization
Spread between 10-Year and 1-Year Treasury rates: T10Y1YT10Y1Y
Spread between the 3-month Treasury bill rate and the effective federal funds rate: TBFFTBFF
Calculate unconditional mean, variance, first p autocovariances and autocorrelations of the GSMAR process.uncond_moments
Perform Wald testWald_test