<p>Sum of squared error to be optimized in the NLS method</p>

internal

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>).

Andrea Bucci

starvars

Vector Logistic Smooth Transition Models Estimation and
Prediction

Giulio Palomba

Eduardo Rossi

Andrea Faragalli

SSQ function

Sum of squared error — SSQ

Sum of squared error

SSQ: Sum of squared error

Description

Usage

Arguments