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Spectral Analysis of Economic Time Series. (PSME-1)

The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for;

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Spectral Analysis of Economic Time Series. (PSME-1)

The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for;

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Spectral Analysis and Time Series, Two-Volume Set

Covers spectral analysis that is closely intertwined with the 'time domain' approach, elementary notions of Hilbert Space Theory, basic;

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Spectral Analysis for Univariate Time Series

Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind;

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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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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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Time Series Analysis

representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the;

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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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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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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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Spectral Analysis

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

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Models for Dependent Time Series

series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful;

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Models for Dependent Time Series

series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful;

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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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Multidimensional Stationary Time Series

. * Provides a unified treatment for time and frequency domain inferences by using machinery of complex and harmonic analysis, spectral and Smith;

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Spectral Analysis of Signals

Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis;

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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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Auditory Spectral Processing

spectral information required for speech and music perception Examines a series of issues that relate to the role of spectral analysis;

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Spectral Analysis of Quantum Hamiltonians

This volume contains surveys as well as research articles broadly centered on spectral analysis. Topics range from spectral continuity for;

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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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Signal Processing with Free Software

leading to Time-frequency analysis. Non-parametric spectral analysis is also discussed as well as signal processing through sampling, resampling;

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Harmonic And Spectral Analysis

the recent developments in spectral analysis and synthesis.;

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Time Series Analysis and Adjustment

analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory;

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Time Series Analysis and Adjustment

analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory;

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Singular Spectrum Analysis

) should be called the analysis of time series using the singular spectrum. Spectral decomposition of matrices is fundamental to much the ory;

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Time Series

backgrounds. The book offers succinct coverage of standard topics in statistical time series - such as forecasting and spectral analysis - in a manner;

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