Cookies?
Library Header Image
LSE Research Online LSE Library Services

Smoothing for discrete-valued time series

Cai, Zongwu, Yao, Qiwei and Zhang, Wenyang (2001) Smoothing for discrete-valued time series. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63 (2). pp. 357-375. ISSN 1369-7412

[img]
Preview
PDF
Download (400Kb) | Preview

Abstract

We deal with smoothed estimators for conditional probability functions of discrete-valued time series {Yt} under two different settings. When the conditional distribution of Yt given its lagged values falls in a parametric family and depends on exogenous random variables, a smoothed maximum (partial) likelihood estimator for the unknown parameter is proposed. While there is no prior information on the distribution, various nonparametric estimation methods have been compared and the adjusted Nadaraya–Watson estimator stands out as it shares the advantages of both Nadaraya–Watson and local linear regression estimators. The asymptotic normality of the estimators proposed has been established in the manner of sparse asymptotics, which shows that the smoothed methods proposed outperform their conventional, unsmoothed, parametric counterparts under very mild conditions. Simulation results lend further support to this assertion. Finally, the new method is illustrated via a real data set concerning the relationship between the number of daily hospital admissions and the levels of pollutants in Hong Kong in 1994–1995. An ad hoc model selection procedure based on a local Akaike information criterion is proposed to select the significant pollutant indices.

Item Type: Article
Official URL: http://www.blackwellpublishing.com/journal.asp?ref...
Additional Information: © 2001 The Royal Statistical Society
Library of Congress subject classification: H Social Sciences > HA Statistics
Sets: Collections > Economists Online
Departments > Statistics
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Funders: National Science Foundation, University of North Carolina, Biotechnology and Biological Science Research Council Engineering, Physical Science Research Council
Projects: DMS 0072400, 96/MM109785
Date Deposited: 30 Jun 2008 11:03
URL: http://eprints.lse.ac.uk/6095/

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only

Downloads

Downloads per month over past year

View more statistics