Vector Logistic Smooth Transition Models Estimation and Prediction R package starvars version 1.1.11 Allows the user to estimate a vector logistic smooth transition autoregressive model via maximum log-likelihood or nonlinear least squares. It further permits to test for linearity in the multivariate framework against a vector logistic smooth transition autoregressive model with a single transition variable. The estimation method is discussed in Terasvirta and Yang (2014, <doi:10.1108/S0731-9053(2013)0000031008>). Also, realized covariances can be constructed from stock market prices or returns, as explained in Andersen et al. (2001, <doi:10.1016/S0304-405X(01)00055-1>). Software Depends: R (>= 4.0) Imports: MASS, ks, zoo, doSNOW, foreach, methods, matrixcalc, optimParallel, parallel, vars, xts, lessR, quantmod Andrea Bucci <andrea.bucci@unimc.it> Comprehensive R Archive Network (CRAN) Andrea Bucci [aut, cre, cph], Giulio Palomba [aut], Eduardo Rossi [aut], Andrea Faragalli [ctb] GPL 2026-01-26 application/tgz https://CRAN.R-project.org/package=starvars doi:10.32614/CRAN.package.starvars