• # ARfit

• Referenced in 38 articles [sw00046]
• analyzing multivariate time series with autoregressive (AR) models. ARfit contains modules to given time series ... eigen modes of a fitted model, and for simulating AR ... processes. ARfit estimates the parameters of AR models from given time series data with ... decomposition of a fitted AR model into eigenmodes and associated oscillation periods, damping times...
• # spTimer

• Referenced in 18 articles [sw24237]
• Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based ... AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015)
• # FitAR

• Referenced in 8 articles [sw08212]
• package FitAR: Subset AR Model Fitting. Comprehensive model building function for identification, estimation and diagnostic ... checking for AR and subset AR models. Two types of subset AR models are supported ... family of subset AR models, denoted by ARp, is formed by taking subet ... original AR coefficients and in the other, denoted by ARz, subsets of the partial autocorrelations...
• # tsDyn

• Referenced in 9 articles [sw12355]
• Regime Switching. Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric ... approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics ... transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR ... range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests...
• # ASAP3

• Referenced in 6 articles [sw24730]
• fits a first-order autoregressive (AR(1)) time series model to the batch means ... until the autoregressive parameter in the AR(1) model does not significantly exceed 0.8. Next ... batch means $t$-ratio based on the AR(1) parameter estimates; and finally ASAP3 delivers...
• # imputeFin

• Referenced in 1 article [sw38295]
• random walk or an autoregressive (AR) model, convenient to model log-prices and log-volumes ... Parameter Estimation of Heavy-Tailed AR Model With Missing Data Via Stochastic EM. IEEE Trans...
• # GLMMarp

• Referenced in 1 article [sw13219]
• contains functions to estimate the GLMM-AR(p) model for analyzing discrete time-series cross ... done only with the R language. The model returns draws of the parameter posteriors selected ... computing the Bayes factor with GLMM-AR(p) output, a function to recover the random...
• # MIXREG

• Referenced in 5 articles [sw24547]
• distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced ... AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also...
• # lsmeans

• Referenced in 7 articles [sw22579]
• many linear, generalized linear, and mixed models. Compute contrasts or linear functions of least-squares ... data with unequal subclass numbers”, Tech Report ARS-20-8, USDA National Agricultural Library ... Population marginal means in the linear model: An alternative to least squares means”, The American...
• # prais

• Referenced in 0 articles [sw15425]
• serial correlation of type AR(1) in a linear model. The procedure is an iterative ... specified model until convergence of rho, i.e. the AR(1) coefficient, is attained. All estimates...
• # DPB

• Referenced in 2 articles [sw23168]
• estimation of the randomeffects dynamic probit model proposed by Heckman (1981b) and its generalisation ... Keane and Sauer (2009) to accommodate AR(1) disturbances. The fixed-effects estimator by Bartolucci...
• # bayeslongitudinal

• Referenced in 1 article [sw37931]
• Models Using Bayesian Methodology. Adjusts longitudinal regression models using Bayesian methodology for covariance structures ... symmetry (SC), autoregressive ones of order 1 AR (1) and autoregressive moving average of order...