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Foundations of Time Series Analysis and Prediction Theory

This book provides a mathematical foundation for prediction theory and time series analysis using the idea of regression (prediction) and;

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Time Series Prediction

The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the;

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Inference and Prediction in Large Dimensions

prediction of continuous time processes. This work is in the Wiley-Dunod Series co-published between Dunod ( www.dunod.com ) and John Wiley and Sons;

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Empirical Likelihood and Quantile Methods for Time Series

understanding the prediction problem that occurs in time series modeling and a contemporary approach of hypothesis testing by the generalized empirical;

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Grammar Based Feature Generation for Time Series Prediction

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation;

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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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Time-aware Conversion Prediction For E-commerce

-commerce. It proposes time-aware conversion prediction models to solve the problem - what products should be recommended for a given period to;

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Fuzzy Logic Augmentation of Neural and Optimization Algorithms Theoretical Aspe

application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization;

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Methodologies for Time Series Prediction and Missing Value Imputation

large databases or are not able to provide the necessary accuracy. This book focuses on two aspects encountered with databases, time series;

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Time Series Models

The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new;

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Time Series Models

The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new;

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Theory and Applications of Time Series Analysis

; time series analysis with computational intelligence; and time series analysis and prediction for other real-world problems. Given this mix;

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Computational Intelligence-based Time Series Analysis

prediction problems that are time-dependent and these problems can be handled through time series analysis. Computational intelligence (CI) is a;

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Time Series Analysis in the Social Sciences

of seasonality, trends, and residuals, to the evaluation and prediction of estimated models. The book also explains smoothing, multiple time series;

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Time Series Analysis in the Social Sciences

of seasonality, trends, and residuals, to the evaluation and prediction of estimated models. The book also explains smoothing, multiple time series;

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Practical Time Series Analysis Prediction with Statistics and Machine Learning

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the;

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Time Series Modelling with Unobserved Components

the software for implementing UCMs. The book's first part discusses introductory time series and prediction theory. Unlike most other;

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Time Series Modelling with Unobserved Components

the software for implementing UCMs. The book's first part discusses introductory time series and prediction theory. Unlike most other books;

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Regression Models For Time Series Analysis

concerning state space models. To conclude, they present a Bayesian approach to prediction and interpolation in spatial data adapted to time series;

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Multi-scale Spectral Analysis in Hydrology

Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding;

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Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles

of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction;

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Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles

of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction;

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Multidimensional Stationary Time Series

This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension;

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