One computationally efficient procedure for obtaining maximum likelihood parameter estimates for an ARMA process is based on the Gram-Schmidt orthogonalization of the space generated by the finite series of observations. This paper shows that the asymptotic distribution of the autocorrelations...

This paper estimates the long-term trends in the daily maxima of tropospheric ozone at six sites around the state of Texas. The statistical methodology we use controls for the effects of meteorological variables because it is known that variables such as temperature, wind speed and humidity...

A Bayesian approach is presented for nonparametric estimation of an additive regression model with autocorrelated errors.

This paper presnets a method for simultaneously estimating a system of nonparametric multiple regressions which may seem unrelated, but where the errors are potentially correlated between equations. We show that the prime advantage of estimating such a 'seemingly unrelated' system of...

A new regression based approach is proposed for modeling marketing databases. The approach is Bayesian and provides a number of significant improvements over current methods. Independent variables can enter into the model in either a parametric or nonparametric manner, significant variables can...