Accession Number:

AD0701464

Title:

STATISTICAL INFERENCE ON TIME SERIES BY RKHS METHODS.

Descriptive Note:

Technical rept.,

Corporate Author:

STANFORD UNIV CALIF DEPT OF STATISTICS

Personal Author(s):

• Parzen,Emanuel

Report Date:

1970-01-20

Pagination or Media Count:

73.0

Abstract:

The theory of time series is studied by probabilists under such names as Gaussian processes and generalized processes, by statisticians who are mainly concerned with modelling discrete parameter time series by finite parameter schemes, and by communication and control engineers who are mainly concerned with the extraction and detection of signals in noise. The aim of this review is to outline the unifying role of reproducing kernel Hilbert spaces RKHS in the theory of time series. There are 13 sections which are divided into an introduction and 4 chapters. The chapter headings are the following Time series and RKHS Parameter estimation and optimization Examples of RKHS and Probability density functionals of normal processes. Author

Descriptors:

• (*TIME SERIES ANALYSIS
• STOCHASTIC PROCESSES)
• INFORMATION THEORY
• CONTROL SYSTEMS
• EXPERIMENTAL DESIGN
• PROBABILITY DENSITY FUNCTIONS
• REGRESSION ANALYSIS
• APPROXIMATION(MATHEMATICS)
• HILBERT SPACE
• REVIEWS

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE