In this paper we consider bayesian semiparametric regression within the generalized linear model framework. Specifically, we study a class of autoregressive time series where the time trend is incorporated in a nonparametrically way. Estimation and inference where performed through Markov Chain...

The aims of this paper are estimate and forecast the Non-Accelerating Inflation Rate of Unemployment, or NAIRU, for Brazilian unemployment time series data. In doing so, we introduce a methodology for estimating mixed additive seasonal autoregressive (MASAR) models, by the Generalized Method of...

This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. Uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of...

This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. Uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of the...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted...