Nonlinear additive ARX models /

Bibliographic Details
Main Authors:	Chen, Rong (Author), Tsay, Ruey S., 1951- (Author)
Corporate Author:	National Science Foundation (U.S.) (sponsoring body.)
Format:	Book
Language:	English
Published:	College Station, Texas : Department of Statistics, Texas A & M University, 1991.
Series:	Technical report (Texas A & M University. Department of Statistics) ; no. 148.
Subjects:	Time-series analysis. Nonlinear theories. Autoregression (Statistics) Regression analysis. Mathematical statistics. Statistics > Nonparametric inference > Nonparametric regression. Additivity Alternating Conditional Expectation (ACE) algorithm BRUTO algorithm Geometric ergodicity Riverflow Variable selection

Description
Abstract:	We consider a class of nonlinear additive autoregressive models with exogenous variables for nonlinear time series analysis. A sufficient condition is given for the geometrical ergodicity of such a time series. We then use the ACE and BRUTO algorithms in conjunction with the procedures of best subset regression and variable selection in regression analysis to build the proposed model. Simulated and real examples are used to illustrate the analysis.
Item Description:	"This research is supported in part by grant DMS9103250 of the National Science Foundation"--Leaf i.
Physical Description:	21 leaves, 9 unnumbered leaves : illustrations ; 28 cm
Bibliography:	Includes bibliographical references (leaves 20-21).