£78.00

Large Sample Inference For Long Memory Processes

Probability & Statistics

Price data last checked 134 day(s) ago - refreshing...

View at Amazon

We'll watch every seller, every day. One email when your price arrives.

It has never been this cheap. We have no record of a lower price.

£78 today · cheaper than every other day in the last 24 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 597 days • 597 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 597 days • 1 price levels

Days at Price

Price Analysis

Most common price: £78 (597 days, 100.0%)

Price range: £78 - £78

Price levels: 1 different prices over 597 days

Description

Box and Jenkins (1970) made the idea of obtaining a stationary time series by differencing the given, possibly nonstationary, time series popular. Numerous time series in economics are found to have this property. Subsequently, Granger and Joyeux (1980) and Hosking (1981) found examples of time series whose fractional difference becomes a short memory process, in particular, a white noise, while the initial series has unbounded spectral density at the origin, i.e. exhibits long memory. Further examples of data following long memory were found in hydrology and in network traffic data while in finance the phenomenon of strong dependence was established by dramatic empirical success of long memory processes in modeling the volatility of the asset prices and power transforms of stock market returns. At present there is a need for a text from where an interested reader can methodically learn about some basic asymptotic theory and techniques found useful in the analysis of statistical inference procedures for long memory processes. This text makes an attempt in this direction. The authors provide in a concise style a text at the graduate level summarizing theoretical developments both for short and long memory processes and their applications to statistics. The book also contains some real data applications and mentions some unsolved inference problems for interested researchers in the field.

Product Specifications

Format: paperback
ASIN: B00GQ20JXY
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Probability & Statistics
Domain: Amazon UK
Release Date: 27 April 2012
Listed Since: 17 November 2013

Large Sample Inference For Long Memory Processes

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Similar Products You Might Like

Long-Memory Time Series: Theory and Methods (Wiley Series in Probability and Statistics)

Nonlinear Time Series: Theory, Methods and Applications with R Examples (Chapman & Hall/CRC Texts in Statistical Science)

Time Series Analysis with Long Memory in View (Wiley Series in Probability and Statistics)

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

Semimartingales and their Statistical Inference: 83 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

NONPARAMETRIC STATISTICAL METHODS AND RELATED TOPICS: A FESTSCHRIFT IN HONOR OF PROFESSOR P K BHATTACHARYA ON THE OCCASION OF HIS 80TH BIRTHDAY

The Practice of Data Analysis: Essays in Honor of John W. Tukey (Princeton Legacy Library): 401

Time Series: Modeling, Computation, and Inference, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

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

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

The Analysis of Time Series: Theory and Practice (Monographs on Statistics and Applied Probability)

Simulation and Inference for Stochastic Processes with YUIMA: A Comprehensive R Framework for SDEs and Other Stochastic Processes (Use R!)

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

Dependence in Probability and Statistics: 187 (Lecture Notes in Statistics, 187)

Extreme Value Theory for Time Series: Models with Power-Law Tails (Springer Series in Operations Research and Financial Engineering)

Time Series: Modeling, Computation, and Inference, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Springer - Selected Works of David Brillinger - Statistics Book

Topics in Stochastic Analysis and Nonparametric Estimation: 145 (The IMA Volumes in Mathematics and its Applications, 145)

Mathematical Foundations of Time Series Analysis: A Concise Introduction

Mathematical Statistics: Basic Ideas and Selected Topics, Volume II: 119 (Chapman & Hall/CRC Texts in Statistical Science)

Uncertainty Analysis in Econometrics with Applications: 200 (Advances in Intelligent Systems and Computing, 200)

Time Series: A Biostatistical Introduction (Oxford Statistical Science Series)

Multivariate Time Series Analysis and Applications (Wiley Series in Probability and Statistics)

Statistical Methods for Stochastic Differential Equations: 124 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)