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Real Time Detection of Turning Points in Financial Time Series

recent financial crisis, institutions are increasingly interested in identifying turning points in financial time series. The accurate and early;

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State-Space Models with Regime Switching

detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with;

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Nonlinear Modelling of High Frequency Financial Time Series

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment;

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Data Mining In Time Series Databases

Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data;

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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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Multivariate Time Series Analysis

An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With;

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Quickest Detection

climate modeling, finance, image analysis, and security. Quickest detection refers to real-time detection of such changes as quickly as possible;

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Real-time PCR

With a variety of detection chemistries, an increasing number of platforms, multiple choices for analytical methods and the jargon emerging;

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Outlier Detection for Temporal Data

detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types;

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Time Series Analysis for the State Space Model with R Stan

, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a;

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Time Series Analysis for the State Space Model with R Stan

, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a;

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Nonlinear Time Series

book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real;

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Nonlinear Time Series

book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real;

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Theory and Applications of Time Series Analysis

forecasting, and time series analysis and prediction in other real-world problems. The book offers readers valuable insights into the different;

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Turning Points in Australian History

event often becomes so only in retrospect and that what seemed like a major turning point at the time often had no real impact at all.;

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Analysis of Time Series Structure

statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory;

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Computational Intelligence-based Time Series Analysis

The sequential analysis of data and information gathered from past to present is called time series analysis. Time series data are of high;

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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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Turning Points in History

In our long human journey, individual and collective, the journey that science calls evolution, many indeed are the turning points. But;

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Fusion Methods for Time-Series Classification

recognition, speech recognition or detection of abnormalities in electrocardiograph signals. In this book, the state-of-the-art in time-series;

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Time Series Analysis and Adjustment

. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover;

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Time Series Analysis and Adjustment

things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to;

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Real-Time Progressive Hyperspectral Image Processing

The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new;

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Financial Econometrics, Mathematics and Statistics

four parts, the text begins with topics related to regression and financial econometrics. Subsequent sections describe time-series analyses;

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Real Time Multi Object Detection and Tracking Using Deep Learning

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Finding Ghosts in Your Data

statistics, clustering, and time series scenarios. Finally, you will compare your anomaly detection service head-to-head with a publicly available;

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