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Forecasting with Dynamic Regression Models

This volume presents the basic concepts and practice of building, using and interpreting single equation dynamic regression models (also;

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Time Series Analysis

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear;

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Time Series Modeling of Neuroscience Data

approach, in which dynamic models of all kinds, such as linear/nonlinear differential equation models and time series models, are used for;

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Time Series Analysis for the Social Sciences

of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the;

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Dynamic Models for Volatility and Heavy Tails

modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic;

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Dynamic Models for Volatility and Heavy Tails

modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic;

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Nonlinear Time Series Analysis

in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods 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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Time Series In High Dimensions

Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides;

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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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Applied Economic Forecasting using Time Series Methods

result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast;

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Regression Models For Time Series Analysis

is not appropriate. This book introduces the reader to newer developments and more diverse regression models and methods for time series analysis;

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Statistical Learning for Big Dependent Data

large and dynamically dependent data sets. The book presents automatic procedures for modelling and forecasting large sets of time series data;

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Bayesian Forecasting and Dynamic Models

of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and;

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Data Mining In Time Series Databases

presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based;

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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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Time Series Models

another level from the first book, focusing on the estimation, testing, and specification of both univariate and multivariate time series models;

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Dynamic Linear Models with R

series analysis is required, although familiarity with basic statistics and R is assumed.;

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Time Series and Dynamic Models

In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics;

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Time Series And Dynamic Models

In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics;

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Dynamic Macroeconomic Theory

equilibrium models. This book describes some general equilibrium models that are dynamic, that have been built to help interpret time-series;

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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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The Stone Lectures in Economics

understanding of the relationship of univariate and multivariate time series forecasting models and dynamic, time series structural econometric models;

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The Stone Lectures in Economics

understanding of the relationship of univariate and multivariate time series forecasting models and dynamic, time series structural econometric models;

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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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Econometrics

methods for program evaluation and a proposal to extend the difference-in-differences estimator to dynamic treatment; empirical estimations of FDI;

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