Sale!

Readings in Unobserved Components Models First Edition by Andrew C Harvey, Tommaso Proietti ISBN 0199278695 9780199278695

Original price was: $50.00.Current price is: $35.00.

Readings in Unobserved Components Models First Edition Andrew C. Harvey Digital Instant Download

Author(s): Andrew C. Harvey, Tommaso Proietti
ISBN(s): 9780199278695, 0199278695
Edition: First Edition
File Details: PDF, 2.71 MB
Year: 2005
Language: english
SKU: EB-1133486 Category: Tags: ,

Readings in Unobserved Components Models First Edition by Andrew C. Harvey, Tommaso Proietti – Ebook PDF Instant Download/Delivery: 0199278695, 9780199278695

Full download Readings in Unobserved Components Models First Edition after payment

 

Product details:

ISBN 10: 0199278695

ISBN 13: 9780199278695 

Author:Andrew C. Harvey, Tommaso Proietti 

This book presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. It contains four parts, three of which concern recent theoretical developments in classical and Bayesian estimation of linear, nonlinear, and non Gaussian UC models, signal extraction and testing, and one is devoted to selected econometric applications.

The first part focuses on the linear state space model; the readings provide insight on prediction theory, signal extraction, and likelihood inference for non stationary and non invertible processes, diagnostic checking, and the use of state space methods for spline smoothing.

Part II deals with applications of linear UC models to various estimation problems concerning economic time series, such as trend-cycle decompositions, seasonal adjustment, and the modelling of the serial correlation induced by survey sample design.

The issues involved in testing in linear UC models are the theme of part III, which considers tests concerned with whether or not certain variance parameters are zero, with special reference to stationarity tests.

Finally, part IV is devoted to the advances concerning classical and Bayesian inference for non linear and non Gaussian state space models, an area that has been evolving very rapidly during the last decade, paralleling the advances in computational inference using stochastic simulation techniques.

The book is intended to give a relatively self-contained presentation of the methods and applicative issues. For this purpose, each part comes with an introductory chapter by the editors that provides a unified view of the literature and the many important developments that have occurred in the last years.

Table of contents:

Signal Extraction and Likelihood Inference for Linear UC Models
1:Introduction
2:Prediction Theory for Autoregressive-Moving Average Processes, P. Burridge and K.F. Wallis
3:Exact Initial Kalman Filtering and Smoothing for Non-stationary Time Series Models, S.J. Koopman
4:Smoothing and Interpolation with the State Space Model, P. de Jong
5:Diagnostic Checking of Unobserved Components in Time Series Models, A.C. Harvey and S.J. Koopman
6:Nonparametric Spline Regression with Autoregressive Moving Average Errors, R. Kohn, C.F. Ansley and C. Wong
Unobserved Components in Economic Time Series
7:Introduction
8:Univariate Detrending Methods with Stochastic Trends, M.W. Watson
9:Detrending, Stylized Facts and the Business Cycle, A.C. Harvey and A. Jaeger
10:Stochastic Linear Trends, Models and Estimators, A. Maravall
11:Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys, D. Pfeffermann
12:The Modelling and Seasonal Adjustment of Weekly Observations, A.C. Harvey, S.J. Koopman and M. Riani
Testing in Unobserved Components Models
13:Introduction
14:Testing for Deterministic Linear Trends in a Times Series, J. Nyblom
15:Are Seasonal Patterns Stable Over Time? A Test for Seasonal Stability, F. Canova and B.E. Hansen
Non-Linear and Non- Gaussian Models
16:Introduction
17:Times Series Models for Count Data or Qualitative Observations, A.C. Harvey and C. Fernandes
18:On Gibbs Sampling for State Space Models, Carter and Kohn
19:The Simulation Smoother, P. de Jong and N. Shephard
20:Likelihood Analysis of Non-Gaussian Measurement Time Series, N. Shephard and M.K. Pitt
21:Time Series Analysis of Non-Gaussian Observations based on State Space Models from both Classical and Bayesian Perspectives, J. Durbin and S.J. Koopman
22:Stochastic Volatility: Liklihood Inference and Comparison with ARCH Models, S. Kim, N. Shephard, and S. Chib
23:On Sequential Monte Carlo Sampling Methods for Bayesian Filtering, A. Doucet, S.J. Godsill, and C. Andrieu

People also search for:

readings in unobserved components models
    
unobserved components model r
    
unobserved components model explained
    
unobserved components model
    
unobserved components model python
    
model un mesa community college

Tags: Andrew C Harvey, Tommaso Proietti, Readings, Unobserved Components Models