With the advance of modern technology, more and more data are being recorded
continuously during a time interval or intermittently at several discrete time points. These are …

Summarizing the effect of many covariates through a few linear combinations is an effective
way of reducing covariate dimension and is the backbone of (sufficient) dimension …

Spectral methods have emerged as a simple yet surprisingly effective approach for
extracting information from massive, noisy and incomplete data. In a nutshell, spectral …

Parameter studies are everywhere in computational science. Complex engineering
simulations must run several times with different inputs to effectively study the relationships …

Sufficient dimension reduction is a rapidly developing research field that has wide
applications in regression diagnostics, data visualization, machine learning, genomics …

Handbook of Regression Methods concisely covers numerous traditional, contemporary,
and nonstandard regression methods. The handbook provides a broad overview of …

Amongmanyexcitingdevelopmentsinstatistic…, nonlineartimeseriesanddata-
analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In …

This book contains a up-to-date overview of nonlinear time series models and their
application to modelling economic relationships. It considers nonlinear models in stationary …

Energy suppliers are facing ever increasing competition, so that factors like quality and
continuity of offered services must be properly taken into account. Furthermore, in the last …

This book is intended to introduce graduate students and practicing professionals to some of
the main ideas and methods of semiparametric and nonparametric estimation in …