Skip Navigation Links

Project Information

SECOND ORDER INFERENCE FOR NONSTATIONARY TIME SERIES

Agency:
NSF

National Science Foundation

Project Number:
1209091
Contact PI / Project Leader:
XIAO, HAN
Awardee Organization:
RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK

Description

Abstract Text:
The proposed research is on second order inferences for causal nonstationary processes. While a causal stationary process can be viewed as generated by filtering a set of past innovations, one can allow the filter to be time-changing, and henceforth introduce nonstationarity. Two sets of problems are considered. First, for linear models with nonstationary errors, the investigator addresses the estimation of covariance matrices of the least square estimates, as well as general M-estimates. Second, the PI studies the estimation of time-varying covariance functions, time-varying spectrum and covariance matrices of the observed time series. Simultaneous inferences of autocovariance functions and spectra can be used to study their patterns and trends, and are also of interests. The study requires several tools to be developed for nonstationary processes, including empirical processes, Gaussian approximations, strong invariance principles and large deviations for quadratic forms.

Stationarity has played an important role in classical time series analysis, which basically says that the overall structure does not change over time. However, in many scientific fields, including economics, engineering, environmental science, finance, and neuroscience etc, it is not realistic to believe the observed time series are stationary. Results from the proposed research will be useful in understanding the nature of the data from various disciplines, making forecasts and conclusions.
Furthermore, the second order inferences in the proposal are general and fundamental, and will facilitate further statistical analysis of nonstationary time series.
Project Terms:
Address; Data; Discipline; Ecology; Economics; Engineering; innovation; interest; Linear Models; Nature; Neurosciences; Pattern; Play; Process; Research; Research Personnel; Role; Series; Structure; Time; Time Series Analysis; tool; trend

Details

Contact PI / Project Leader Information:
Name:  XIAO, HAN
Other PI Information:
Not Applicable
Awardee Organization:
Name:  RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK
City:  NEW BRUNSWICK    
Country:  UNITED STATES
Congressional District:
State Code:  NJ
District:  06
Other Information:
Fiscal Year: 2012
Award Notice Date:
DUNS Number: 001912864
Project Start Date: 15-Aug-2012
Budget Start Date:
CFDA Code: 47.049
Project End Date: 31-Jul-2015
Budget End Date:
Agency: ?

Agency: The entity responsible for the administering of a research grant, project, or contract. This may represent a federal department, agency, or sub-agency (institute or center). Details on agencies in Federal RePORTER can be found in the FAQ page.

National Science Foundation
Project Funding Information for 2012:
Year Agency

Agency: The entity responsible for the administering of a research grant, project, or contract. This may represent a federal department, agency, or sub-agency (institute or center). Details on agencies in Federal RePORTER can be found in the FAQ page.

FY Total Cost
2012 NSF

National Science Foundation

$27,221

Results

i

It is important to recognize, and consider in any interpretation of Federal RePORTER data, that the publication and patent information cannot be associated with any particular year of a research project. The lag between research being conducted and the availability of its results in a publication or patent award varies substantially. For that reason, it's difficult, if not impossible, to associate a publication or patent with any specific year of the project. Likewise, it is not possible to associate a publication or patent with any particular supplement to a research project or a particular subproject of a multi-project grant.

ABOUT FEDERAL REPORTER RESULTS

Publications: i

Click on the column header to sort the results

PubMed = PubMed PubMed Central = PubMed Central Google Scholar = Google Scholar

Patents: i

Click on the column header to sort the results

Similar Projects

Download Adobe Acrobat Reader:Adobe Acrobat VERSION: 3.41.0 Release Notes
Back to Top