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Recursive Estimation and Time Series Analysis

in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for;

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Introduction to Time Series Modeling

. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the;

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Introduction to Time Series Modeling with Applications in R

likelihood method, recursive estimation for state-space models and model selection by AIC. Along with the standard stationary time series models;

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Introduction To Statistical Time Series

analysis Spectral theory and filtering Large sample theory Estimation of the mean and autocorrelations Estimation of the spectrum Parameter;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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Economic Dynamics in Discrete Time

control, policy analysis in dynamic New Keynesian models with the zero lower bound on interest rates, and Bayesian estimation of dynamic;

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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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Time Series in Economics and Finance

This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers;

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Time Series in Economics and Finance

This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers;

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Simulation and Analysis of Modern Power Systems

any online entitlements included with the product Master the modeling, analysis, and simulation of today's power systems This;

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Recursive Identification and Parameter Estimation

Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation;

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Recursive Identification and Parameter Estimation

Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation;

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Capital Theory Equilibrum Analysis and Recursive Utility

In Capital Theory and Equilibrium Analysis and Recursive Utility, Robert Becker and John Boyd have synthesized their previously unpublished;

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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 Analysis with Long Memory in View

foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework;

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Economic Time Series

Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and;

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Model-Based Processing for Underwater Acoustic Arrays

method as a Bayesian processor. Short expositions of estimation theory and acoustic array theory are presented, followed by a presentation of the;

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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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Dynamic Vision for Perception and Control of Motion

representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation;

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Identification Of Time-Varying Processes

control and failure detection). The processes also assist signal processing in areas such as adaptive noise reduction, prediction of time series;

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RLS Wiener Smoother from Randomly Delayed Observations in Linear Discrete-Time Systems

input noise and the input matrix in the state equation, in comparison with the estimation technique by the Kalman filter. Hence, the RLS Wiener;

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Unit Roots, Cointegration, and Structural Change

Time series analysis has undergone many changes in recent years with the advent of unit roots and cointegration. Maddala and Kim present a;

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Option Pricing and Estimation of Financial Models with R

covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book;

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Handbook Of Applied Econometrics And Statistical Inference

, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering;

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Handbook Of Applied Econometrics And Statistical Inference

, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering;

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Unobserved Components and Time Series Econometrics

of unobserved components time series models; and time series econometrics and estimation and testing. These types of time series models have seen wide;

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