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Modelling Non-Linear Time Series ATE
0 - Default Title
Description
Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter is devoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.
Readership: Academics, researchers, graduates and advanced undergraduates of econometrics, particularly academics in time series econometrics.
Product details
Edition:
illustrated
Number of Pages:
586
Release Date:
2011-02-11
Publication Date:
2010-12-16
Publisher:
OUP Oxford
Languages:
Original:
English
ISBN10:
0199587140
ISBN13:
9780199587148
GPSR Manufacturer Reference:
Weight:
1036 g
Height:
161 cm
Width:
240 cm
Thickness:
36 cm
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