Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model

[Up] [Top]

Documentation for package ‘uGMAR’ version 3.3.1

Help Pages

A C D E F G I L M N P Q R S T U W

-- A --

add_data Add data to object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model
add_dfs Add random dfs to a vector
all_pos_ints Check whether all arguments are strictly positive natural numbers
alt_gsmar Construct a GSMAR model based on results from an arbitrary estimation round of 'fitGSMAR'

-- C --

calc_gradient Calculate gradient or Hessian matrix
calc_hessian Calculate gradient or Hessian matrix
change_parametrization Change parametrization of a parameter vector
change_regime Change the specified regime of parameter vector to the given regime-parameter vector
check_and_correct_data Check that the data is set correctly and correct if not
check_constraint_mat Check the constraint matrices
check_data Check that given object contains data
check_gsmar Check that given object has class attribute 'gsmar'
check_model Check that the argument 'model' is correctly specified.
check_params_length Check that the parameter vector has the correct dimension
check_pM Check that p and M are correctly set
condmomentPlot DEPRECATED, USE 'cond_moment_plot' INSTEAD! Conditional mean or variance plot for GMAR, StMAR, and G-StMAR models
condMoments DEPRECATED, USE 'cond_moments' INSTEAD! Calculate conditional moments of GMAR, StMAR, or G-StMAR model
cond_moments Calculate conditional moments of GMAR, StMAR, or G-StMAR model
cond_moment_plot Conditional mean or variance plot for GMAR, StMAR, and G-StMAR models

-- D --

diagnosticPlot DEPRECATED, USE 'diagnostic_plot' INSTEAD! Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR models
diagnostic_plot Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR models

-- E --

extract_regime Extract regime from a parameter vector

-- F --

fitGSMAR Estimate Gaussian or Student's t Mixture Autoregressive model
format_valuef Function factory for formatting values

-- G --

GAfit Genetic algorithm for preliminary estimation of GMAR, StMAR, or G-StMAR model
get_alpha_mt Get mixing weights alpha_mt (this function is for internal use)
get_ar_roots Calculate absolute values of the roots of the AR characteristic polynomials
get_foc Calculate gradient or Hessian matrix
get_gradient Calculate gradient or Hessian matrix
get_hessian Calculate gradient or Hessian matrix
get_IC Calculate AIC, HQIC and BIC
get_minval Returns the default smallest allowed log-likelihood for given data.
get_regime_autocovs Calculate regime specific autocovariances *gamma*_{m,p}
get_regime_means Calculate regime specific means mu_{m}
get_regime_vars Calculate regime specific variances gamma_{m,0}
get_soc Calculate gradient or Hessian matrix
get_test_Omega Generate the covariance matrix Omega for quantile residual tests
get_varying_h Get differences 'h' which are adjusted for overly large degrees of freedom parameters
GSMAR Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model

-- I --

isStationary DEPRECATED, USE 'is_stationary' INSTEAD! Check the stationary condition of specified GMAR, StMAR, or G-StMAR model.
is_identifiable Check the stationarity and identification conditions of specified GMAR, StMAR, or G-StMAR model.
is_stationary Check the stationary condition of specified GMAR, StMAR, or G-StMAR model.
is_stationary_int Check the stationarity and identification conditions of specified GMAR, StMAR, or G-StMAR model.
iterate_more Maximum likelihood estimation of GMAR, StMAR, or G-StMAR model with preliminary estimates

-- L --

logLik.gsmar Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model
loglikelihood Compute the log-likelihood of GMAR, StMAR, or G-StMAR model
loglikelihood_int Compute the log-likelihood of GMAR, StMAR, or G-StMAR model
LR_test Perform likelihood ratio test

-- M --

M10Y1Y Spread between 10-Year and 1-Year treasury rates: M10Y1Y
mixingWeights DEPRECATED, USE 'mixing_weights' INSTEAD! Calculate mixing weights of GMAR, StMAR or G-StMAR model
mixing_weights Calculate mixing weights of GMAR, StMAR or G-StMAR model
mixing_weights_int Calculate mixing weights of a GMAR, StMAR, or G-StMAR model

-- N --

n_params Calculate the number of parameters

-- P --

parameter_checks Check the parameter vector is specified correctly
pick_alphas Pick mixing weights parameters from parameter vector
pick_dfs Pick degrees of freedom parameters from a parameter vector
pick_pars Pick phi_0 (or mu), AR-coefficients, and variance parameters from a parameter vector
pick_phi0 Pick phi0 or mean parameters from parameter vector
plot.gsmar Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model
plot.gsmarpred Plot method for class 'gsmarpred' objects
plot.qrtest Quantile residual tests for GMAR, StMAR , and G-StMAR models
predict.gsmar Forecast GMAR, StMAR, or G-StMAR process
print.gsmar Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model
print.gsmarpred Print method for class 'gsmarpred' objects
print.gsmarsum Print method from objects of class 'gsmarsum'
print.lr Perform likelihood ratio test
print.qrtest Quantile residual tests for GMAR, StMAR , and G-StMAR models
print.wald Perform Wald test
profile_logliks Plot profile log-likelihoods around the estimates

-- Q --

quantileResidualPlot DEPRECATED, USE 'quantile_residual_plot' INSTEAD! Plot quantile residual time series and histogram
quantileResiduals DEPRECATED, USE 'quantile_residuals' INSTEAD! Compute quantile residuals of GMAR, StMAR, or G-StMAR model
quantileResidualTests DEPRECATED, USE 'quantile_residual_tests' INSTEAD! Quantile residual tests for GMAR, StMAR , and G-StMAR models
quantile_residuals Compute quantile residuals of GMAR, StMAR, or G-StMAR model
quantile_residuals_int Compute quantile residuals of GMAR, StMAR, or G-StMAR model
quantile_residual_plot Plot quantile residual time series and histogram
quantile_residual_tests Quantile residual tests for GMAR, StMAR , and G-StMAR models

-- R --

randomIndividual DEPRECATED, USE 'random_ind' OR 'smart_ind' INSTEAD! Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
random_arcoefs Create random AR coefficients
random_ind Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
random_ind_int Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
random_regime Create random regime parameters
reform_constrained_pars Reform parameter vector with linear constraints to correspond non-constrained parameter vector.
reform_parameters Reform any parameter vector into standard form.
reform_restricted_pars Reform parameter vector with restricted autoregressive parameters to correspond non-restricted parameter vector.
regime_distance Calculate "distance" between two regimes
remove_all_constraints Transform constrained and restricted parameter vector into the regular form
residuals.gsmar Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model

-- S --

simudata Simulated data
simulateGSMAR Simulate values from GMAR, StMAR, and G-StMAR processes
smartIndividual DEPRECATED, USE 'random_ind' OR 'smart_ind' INSTEAD! Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
smart_ind Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
smart_ind_int Create random GMAR, StMAR, or G-StMAR model compatible parameter vector
sort_components Sort the mixture components of a GMAR, StMAR, or G-StMAR model
standard_errors Calculate standard errors for estimates of a GMAR, StMAR, or G-StMAR model
stmarpars_to_gstmar Transform a StMAR or G-StMAR model parameter vector to a corresponding G-StMAR model parameter vector with large dfs parameters reduced.
stmar_to_gstmar Estimate a G-StMAR model based on a StMAR model with large degrees of freedom parameters
summary.gsmar Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model
swap_parametrization Swap the parametrization of object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model

-- T --

T10Y1Y Spread between 10-Year and 1-Year treasury rates: T10Y1Y

-- U --

uGMAR uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models
uncond_moments Calculate unconditional mean, variance, first p autocovariances and autocorrelations of the GSMAR process.
uncond_moments_int Calculate unconditional mean, variance, and the first p autocovariances and autocorrelations of a GSMAR process.

-- W --

Wald_test Perform Wald test
warn_ar_roots Warn about near-unit-roots in some regimes
warn_dfs Warn about large degrees of freedom parameter values