Hart, Jeffrey (1996) Some automated methods of smoothing time-dependent data. Journal of Nonparametric Statistics, 6 (2-3). pp. 115-142. DOI: https://doi.org/10.1080/10485259608832667
Full text not available from this repository.Abstract
Nonparametric function estimation based upon time-dependent data is a challenging problem to both the data analyst and the theoretician. This paper serves as an introduction to the problem and discusses some of the approaches that have been proposed for smoothing autocorrelated data. A principal theme will be accounting for correlation in the data driven choice of a function estimator's smoothing parameter. Data-driven smoothing is considered in various settings including probability density estimation, repeated measures data, and time series trend estimation. Both applications and theoretical issues are addressed, and some open problems will be discussed.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Kernel estimators, mean integrated squared error, cross-validation, plug-in rules, autoregression, transition densities, block wise cross-validation, prequential analysis, time series cross-validation |
| Subjects: | Methodology > Method and procesing > Collective properties of seismicity Methodology > Method and procesing |
| Project: | IS-EPOS project |