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Time Series Models

Time Series Models is a companion volume to Andrew Harvey's highly successful Econometric Analysis of Time Series. It takes students to;

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Non-Gaussian Autoregressive-Type Time Series

This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates;

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Advanced Time Series Data Analysis

forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate;

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Unobserved Components and Time Series Econometrics

This volume presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and;

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A Course in Time Series Analysis

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time;

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Introduction to Time Series Modeling

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates;

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Time Series and Panel Data Econometrics

This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial;

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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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Time Series Models for Business and Economic Forecasting

The econometric analysis of economic and business time series is a major field of research and application. The last few decades have;

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Time Series Analysis for the Social Sciences

Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties;

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Nonlinear Time Series Analysis

A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series;

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Hidden Markov and Other Models for Discrete-Valued Time Series

Discrete-valued time series are common in practice, but methods for their analysis are not well-known. In recent years, methods have been;

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Multivariate Time Series Analysis

An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With;

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Hands-On Time Series Analysis with R

Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features Perform time series;

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Time Series Models for Business and Economic Forecasting

textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a;

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Time Series Models for Business and Economic Forecasting

textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a;

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The Analysis of Time Series

, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral;

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The Analysis of Time Series

, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral;

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Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods

Get better insights from time-series data and become proficient in model performance analysis Key Features Explore popular and modern;

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Applied Time Series

Applied Time Series: Analysis and Forecasting provides the theories methods and tools for necessary modeling and forecasting of time series;

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Applied Econometric Time Series

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Applied Econometric Times Series;

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Time Series

Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and;

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Time Series

Focusing on Bayesian approaches and computations using analytic and simulation-based methods for inference, Time Series: Modeling;

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Recent Advances in Estimating Nonlinear Models

number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and;

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Multivariate Time Series Analysis and Applications

An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the;

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Regression Models For Time Series Analysis

A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time;

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Time Series Analysis

-world time series, and by developing a complete approach to model building, estimation, forecasting and control. - Mathematical Reviews;

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