We introduce a two-step procedure for more efficient nonparametric prediction of a strictly stationary process admitting an ARMA representation. The procedure is based on the estimation of the ARMA representation, followed by a nonparametric regression where the ARMA residuals are used as...

Using a microbased superpopulation approach (see Cassel and Lundquist (1991), (1990))the question of optimal predictors of a population total of AR(1) series is analysed. Only a sample of the individual timeseries in the population is observed. From the sample the population total is predicted....

In a typical empirical modeling context, the data generating process (DGP) of a time series is assumed to be known up to a finite-dimensional parameter. In such cases, Rissanen's (1986) theorem provides a lower bound for the empirically achievable distance between all possible data-based models...

Using a microbased superpopulation approach some aspects of optimal prediction of aggregated AR(1) processes are studied.

One way to interpret the classical secretary problem (CSP) is to consider it as a special case of the following problem. We observe n independent indicator variables I1,I2,…,In sequentially and we try to stop on the last variable being equal to 1. If Ik=1 it means that the kth observed...

A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or...