We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. Limit results are given for estimation of the mean, autocovariance and autocorrelation functions within the broad region of stationarity that includes near boundary...

This paper considers a partially linear model of the form y = x beta + g(t) + e, where beta is an unknown parameter vector, g(.) is an unknown function, and e is an error term. Based on a nonparametric estimate of g(.), the parameter beta is estimated by a semiparametric weighted least squares...

We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. The concept of stationarity is refined, allowing for sample size dependence in the array and paying special attention to the rate at which the boundary unit root case is...

The paper considers the block sampling method for long-range dependent processes. Our theory generalizes earlier ones by Hall et al. (1998) [11] on functionals of Gaussian processes and Nordman and Lahiri (2005) [16] on linear processes. In particular, we allow nonlinear transforms of linear...

<Para ID="Par1">Integer-valued time series models have been a recurrent theme considered in many papers in the last three decades, but only a few of them have dealt with models on <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$${\mathbb {Z}}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi mathvariant="double-struck">Z</mi> </math> </EquationSource> </InlineEquation> (that is, including both negative and positive integers). Our aim in this paper is to introduce a...</equationsource></equationsource></inlineequation></para>