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✨
DESCRIPTION |NEWS
card.svg |card.png
uGMAR/json (API)

# 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:

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

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

Target	Result	Time
linux-devel-x86_64	OK	151
source / vignettes	OK	202
linux-release-x86_64	OK	152
macos-release-arm64	OK	157
macos-oldrel-arm64	OK	127
windows-devel	OK	107
windows-release	OK	96
windows-oldrel	OK	97
wasm-release	OK	113

Exports:add_data alt_gsmar calc_gradient calc_hessian cond_moment_plot cond_moments diagnostic_plot fitGSMAR GAfit get_ar_roots get_foc get_gradient get_hessian get_regime_autocovs get_regime_means get_regime_vars get_soc GSMAR is_stationary iterate_more loglikelihood LR_test mixing_weights profile_logliks quantile_residual_plot quantile_residual_tests quantile_residuals random_ind smart_ind stmar_to_gstmar stmarpars_to_gstmar swap_parametrization uncond_moments Wald_test

Dependencies:Brobdingnag gsl lattice Matrix pbapply

uGMAR: A Family of Mixture Autoregressive Models in R

Rendered fromuGMARpaper.Rnwusingutils::Sweave

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

Help page	Topics
uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models	uGMAR-package uGMAR
Add data to object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model	add_data
Construct a GSMAR model based on results from an arbitrary estimation round of 'fitGSMAR'	alt_gsmar
Calculate gradient or Hessian matrix	calc_gradient calc_hessian get_foc get_gradient get_hessian get_soc
Conditional mean or variance plot for GMAR, StMAR, and G-StMAR models	cond_moment_plot
Calculate conditional moments of GMAR, StMAR, or G-StMAR model	cond_moments
Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR models	diagnostic_plot
Estimate Gaussian or Student's t Mixture Autoregressive model	fitGSMAR
Genetic algorithm for preliminary estimation of GMAR, StMAR, or G-StMAR model	GAfit
Calculate absolute values of the roots of the AR characteristic polynomials	get_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 model	GSMAR 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 estimates	iterate_more
Compute the log-likelihood of GMAR, StMAR, or G-StMAR model	loglikelihood
Perform likelihood ratio test	LR_test
Spread between 10-Year and 1-Year Treasury rates: M10Y1Y	M10Y1Y
Calculate mixing weights of GMAR, StMAR or G-StMAR model	mixing_weights
Pick phi_0 (or mu), AR-coefficients, and variance parameters from a parameter vector	pick_pars
Plot method for class 'gsmarpred' objects	plot.gsmarpred
Quantile residual tests for GMAR, StMAR , and G-StMAR models	plot.qrtest print.qrtest quantile_residual_tests
Forecast GMAR, StMAR, or G-StMAR process	predict.gsmar
Print method for class 'gsmarpred' objects	print.gsmarpred
Print method from objects of class 'gsmarsum'	print.gsmarsum
Plot profile log-likelihoods around the estimates	profile_logliks
Plot quantile residual time series and histogram	quantile_residual_plot
Compute quantile residuals of GMAR, StMAR, or G-StMAR model	quantile_residuals
Create random GMAR, StMAR, or G-StMAR model compatible parameter vector	random_ind smart_ind
Reform any parameter vector into standard form.	reform_parameters
Simulated data	simudata
Simulate obsercations from GMAR, StMAR, and G-StMAR processes	simulate.gsmar
Estimate a G-StMAR model based on a StMAR model with large degrees of freedom parameters	stmar_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 model	swap_parametrization
Spread between 10-Year and 1-Year Treasury rates: T10Y1Y	T10Y1Y
Spread between the 3-month Treasury bill rate and the effective federal funds rate: TBFF	TBFF
Calculate unconditional mean, variance, first p autocovariances and autocorrelations of the GSMAR process.	uncond_moments
Perform Wald test	Wald_test

Package: uGMAR 3.6.1

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

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