Asymptotics, Nonparametrics, and Time Series

Some examples of empirical fourier analysis in scientific problems; modeling and inference for periodically correlated time series; modeling time series of count data; seasonal and cyclical long memory; nonparametric specification procedures for time series; parameter estimation and model selection for multistep prediction of a time series - a review; nonlinear estimation for time series observed on arrays; some contributions to multivariate nonlinear time series and to bilinear models; optimal testing for semiparametric AR models - from Gaussian Lagrange multipliers to autoregression rank scores and adaptive tests; statistical analysis based on functionals of nonparametric spectral density estimators; efficient estimation in a semiparametric additive regression model with ARMA errors; efficient estimation in Markov chain models - an introduction; nonparametric functional estimation - an overview; minimum distance and nonparametric dispersion functions; estimators of changes; on inverse estimation; approaches for semiparametric Bayesian regression; consistency issues in Bayesian nonparametrics; breakdown theory for estimators based on bootstrap and other resampling schemes; on second-order properties of the stationary bootstrap method for studentized statistics; convergence to equilibrium of random dynamical systems generated by IID monotone maps, with applications to economics; chi-squared tests of goodness-of-fit for dependent observations; positive and negative dependence with some statistical applications; second-order information loss due to nuisance parameters - a simple measure. Appendix: publications of Madan Lal Puri.