Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Henry L. Gray"'
Publikováno v:
Journal of Probability and Statistics, Vol 2013 (2013)
For nonstationary time series consisting of multiple time-varying frequency (TVF) components where the frequency of components overlaps in time, classical linear filters fail to extract components. The G-filter based on time deformation has been deve
Externí odkaz:
https://doaj.org/article/df373b7717174cf9b87d89f00e83e6bb
Publikováno v:
Journal of Probability and Statistics, Vol 2012 (2012)
The classical linear filter can successfully filter the components from a time series for which the frequency content does not change with time, and those nonstationary time series with time-varying frequency (TVF) components that do not overlap. How
Externí odkaz:
https://doaj.org/article/ef411caf968748ccb5ddfb3a455a51d8
Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and exte
Publikováno v:
Journal of Signal and Information Processing. :491-501
The classical linear filter is able to extract components from multi-component stochastic processes where the frequencies of components do not overlap over time, but fail for those processes where the frequencies overlap over time. In this paper, we
Autor:
Henry L. Gray, Chu-Ping C. Vijverberg
Publikováno v:
Journal of Forecasting. 28:293-315
This paper introduces discrete Euler processes and shows their application in detecting and forecasting cycles in non-stationary data where periodic behavior changes approximately linearly in time. A discrete Euler process becomes a classical station
Publikováno v:
The American Statistician. 63(4):335-342
Most introductory time series analysis courses and texts designed for students in statistics, engineering, applied sciences, econometrics, and finance are sorely lacking when it comes to providing much depth of understanding about the basic features
Publikováno v:
Bulletin of the Seismological Society of America. 97:1196-1203
In this article we introduce the use of time-transformation methods for analyzing signals with time-varying frequencies. We show that these techniques can be usefully applied to the Lg waves of earthquakes and explosions for purposes of deriving disc
Publikováno v:
Computational Statistics & Data Analysis. 51:1997-2028
Methods such as wavelets, short term Fourier transforms and time deformation [Gray and Zhang, 1988. On a class of nonstationary processes. J. Time Ser. Anal. 9(2), 133-154 and Gray, Vijverberg and Woodward, 2005. Nonstationary data analysis by time d
Publikováno v:
Communications in Statistics - Theory and Methods. 35:2245-2262
We introduce Euler(p, q) processes as an extension of the Euler(p) processes for purposes of obtaining more parsimonious models for non stationary processes whose periodic behavior changes approximately linearly in time. The discrete Euler(p, q) mode