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Multivariate Modelling of Non Stationary Economic Time Series

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on;

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Modelling Non-Stationary Economic Time Series

Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of ec;...

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Modelling Non-Stationary Economic Time Series

Co-integration, equilibrium and equilibrium correction are key concepts in modern applications ;...

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Non-Gaussian Autoregressive-Type Time Series

-series models into different groups such as linear stationary models with non-Gaussian innovations, linear stationary models with non-Gaussian;

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Modelling Nonlinear Economic Time Series

This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic;

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Modelling the Probability Distribution of Stock Price Changes

financial time series such as volume-volatility relationship, financial leverage effect, seasonality, and non normal probability distributions.;

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Forecasting Economic Time Series

relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject;

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Forecasting Economic Time Series

relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject;

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Modelling Trends and Cycles in Economic Time Series

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic;

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Modelling Trends and Cycles in Economic Time Series

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic;

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Modelling Trends and Cycles in Economic Time Series

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic;

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Introduction to Time Series Modeling with Applications in R

stationary and nonstationary time series models and tools for estimating and utilizing them. The goal of this book is to enable readers to build;

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Time Series Econometrics

of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series;

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Digital Spectral Analysis

in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution;

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TIME SERIES ANALYSIS AND MACROECONOMETRIC MODELLING

of economic time series, large-scale macroeconometric modelling, and the interface between them.The first part deals with time-series econometrics and;

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Non-Stationary Electromagnetics

This book is devoted to investigations of non-stationary electromagnetic processes. It offers a good opportunity to introduce the Volterra;

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Long Memory in Economics

distant obs- vations. We formalize this dependence by assuming that the autocorrelation function of these stationary series decays very slowly;

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Time Series Modelling in Earth Sciences

Including the latest theories and applications of time series modelling, this book is intended for students, faculties and professionals;

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Introduction to Time Series Modeling

stationary time series models, such as AR and ARMA models, as well as nonstationary time series models, including the locally stationary AR model;

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An Introduction to Applied Econometrics

central distinction between stationary and nonstationary time series, which is of crucial importance in many areas of analysis, especially;

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Time Series Analysis and Forecasting by Example

, including: * Graphical tools in time series analysis * Procedures for developing stationary, non-stationary, and seasonal models * How to choose the;

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Forecasting Economic Time Series using Locally Stationary Processes

Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying;

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Recent Econometric Techniques for Macroeconomic and Financial Data

non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore;

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Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals

are able to extract information from non-stationary signals such as heart sounds and power electric signals. The methods proposed focus on the;

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Non-Stationary Electromagnetics

This book is devoted to the investigations of non-stationary electromagnetic processes. The investigations are undertaken analytically;

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Real Options Valuation

often non-stationary and exhibit non-normally distributed returns. Subsequently, more realistic stochastic volatility, jump diffusion, and Levy;

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Econometrics

Two main purposes of econometrics are to give empirical content to economic theory by formulating economic models in testable form and to;

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