Predictions in Time Series Using Regression Models - Image 1

£90.08

Springer Predictions in Time Series Using Regression Models

Name: Predictions in Time Series Using Regression Models
Brand: Springer
Price: 90.08 GBP
Availability: InStock

9780387953502

Econometrics

Price History & Forecast

Last 14 days • 14 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 14 days • 1 price levels

Days at Price

Price Analysis

Most common price: £90 (14 days, 100.0%)

Price range: £90 - £90

Price levels: 1 different prices over 14 days

Description

Books on time series models deal mainly with models based on Box-Jenkins methodology which is generally represented by autoregressive integrated moving average models or some nonlinear extensions of these models, such as generalized autoregressive conditional heteroscedasticity models. Statistical inference for these models is well developed and commonly used in practical applications, due also to statistical packages containing time series analysis parts. The present book is based on regression models used for time series. These models are used not only for modeling mean values of observed time se ries, but also for modeling their covariance functions which are often given parametrically. Thus for a given finite length observation of a time series we can write the regression model in which the mean value vectors depend on regression parameters and the covariance matrices of the observation depend on variance-covariance parameters. Both these dependences can be linear or nonlinear. The aim of this book is to give an unified approach to the solution of statistical problems for such time series models, and mainly to problems of the estimation of unknown parameters of models and to problems of the prediction of time series modeled by regression models.

Product Specifications

Brand: Springer
Model: 9780387953502
Format: hardcover
ASIN: 0387953507
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 12 April 2002
Listed Since: 08 February 2007

Barcode

No barcode data available

Springer Predictions in Time Series Using Regression Models

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Time Series Econometrics (Springer Texts in Business and Economics)

Elements of Nonlinear Time Series Analysis and Forecasting (Springer Series in Statistics)

Analysis of Integrated and Cointegrated Time Series with R (Use R!)

Regression: Models, Methods and Applications

Time Series Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Modelling Nonlinear Economic Time Series (Advanced Texts In Econometrics)

Regression: Models, Methods and Applications

An Introduction to State Space Time Series Analysis (Practical Econometrics)

Applied Economic Forecasting using Time Series Methods

Introduction to Modern Time Series Analysis (Springer Texts in Business and Economics)

Nonlinear Time Series: Nonparametric and Parametric Methods (Springer Series in Statistics)

Introduction to Modern Time Series Analysis (Springer Texts in Business and Economics)

Model-Free Prediction and Regression: A Transformation-Based Approach to Inference (Frontiers in Probability and the Statistical Sciences)

New Introduction to Multiple Time Series Analysis

Elements of Multivariate Time Series Analysis (Springer Series in Statistics)

Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series: 186 (Lecture Notes in Statistics, 186)

Non-Linear Time Series: Extreme Events and Integer Value Problems

Statistical Analysis of Climate Series: Analyzing, Plotting, Modeling, and Predicting with R

An Introduction to Statistical Data Science: Theory and Models

Time Series Econometrics (In 2 Volumes)

Time Series in Economics and Finance

Time-Series Forecasting

Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics: 979 (Studies in Computational Intelligence, 979)

Time Series Analysis: With Applications in R (Springer Texts in Statistics)