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Spectral Analysis and Time Series, Two-Volume Set

probability theory, and practical analysis of time series data.;

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Spectral Analysis for Univariate Time Series

spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography;

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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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Spectral Analysis of Signals

astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the;

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Time Series Analysis in Climatology and Related Sciences

contains many examples in different areas of time series analysis such as autoregressive modelling and spectral analysis, linear extrapolation;

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Multi-scale Spectral Analysis in Hydrology

series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet;

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Periodically Correlated Random Sequences

Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use;

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Spectral Analysis of Time-Series Data

This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both;

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Time Series Analysis and its Applications

analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods;

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Models for Dependent Time Series

approaches with spectral methods for identifying causal dependence between time series. Web ResourceA supplementary website provides the data;

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Models for Dependent Time Series

approaches with spectral methods for identifying causal dependence between time series. Web Resource A supplementary website provides the data sets;

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Multivariate Time Series Analysis and Applications

, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral;

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Time-Series Analysis and Cyclostratigraphy

, cross-spectral analysis, filtering, complex demodulation, wavelet and singular spectrum analysis. Practical problems of time-series analysis;

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Climate Time Series Analysis

, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step;

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Time Series with Mixed Spectra

extensions of the traditional periodogram. Complete in breadth and depth, this book explains how to perform the spectral analysis of time series;

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Time Series with Mixed Spectra

extensions of the traditional periodogram. Complete in breadth and depth, this book explains how to perform the spectral analysis of time series;

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Data Analysis Methods in Physical Oceanography

methods and error handling, analysis of spatial data fields, and time series analysis methods. The revised Third Edition updates the;

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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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Using Time Series to Analyze Long-Range Fractal Patterns

integrated moving average models, and power spectral density analysis. He demonstrates the methods through two kinds of examples: simulations that;

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Time Series Analysis

practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates;

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Digital Spectral Analysis MATLAB (R) Software User Guide

This user guide serves as a companion to Digital Spectral Analysis, Second Edition (Dover Publications, 2019), illustrating all the text's;

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Financial Econometrics

This book provides an essential toolkit for all students wishing to know more about the modelling and analysis of financial data;

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Financial Econometrics

This book provides an essential toolkit for all students wishing to know more about the modelling and analysis of financial data;

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Spectral Analysis

-parametric methods, which are still the most widely used in practical spectral analysis.;

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Digital Spectral Analysis with Applications

Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral;

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The Analysis of Time Series

Since 1975, The Analysis of Time Series: An Introduction has introduced legions of statistics students and researchers to the theory and;

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