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Correlation of Data Series. A Scientific Study on the Selection of Meaningful Variables and Functions for the Separation of Trends, Cyclic Parts and Scatter from Data Series

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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 and Spatial Analysis of Crop Yield

correlation information can be utilized to model and forecast yield and related variables. The conclusion from this research clearly emphasizes the;

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Basic Data Analysis for Time Series with R

Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative;

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Trends and Changes in Hydroclimatic Variables

serial auto-correlation in data) for assessing trends in different hydroclimatic variables (e.g. pre-whitening methods). This book offers a;

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THE ECONOMETRICS OF PANEL DATA

This important reference work offers readers, researchers and students a thoughtful, balanced selection of core articles from the;

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Robust Correlation Theory & Aplications

This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions;

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Hands-On Time Series Analysis with R

of extracting meaningful insights from, and revealing patterns in, time series data using statistical and data visualization approaches. These insights;

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Advanced Time Series Data Analysis

the worst and the best forecast models among each set of the models of a specific independent variable. Advanced Time Series Data Analysis;

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Practical Business Analytics Using SAS

on the go. Its toolboxes for business analytics and business intelligence can mine, alter, manage and retrieve data from a variety of data;

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Quantitative Research In Linguistics

, or for postgraduates embarking on linguistic research projects. Research Methods in Linguistics is a new series from Continuum providing a;

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Excel 2007 Charts Made Easy

the next level with help from this hands-on guide. Excel 2007 Charts Made Easy shows you how to upgrade from simple pie and bar charts to rich;

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Data Preparation for Analytics Using SAS

series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types;

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Advanced Calculus

already completed a one-year course in elementary calculus, it defers the introduction of functions of several variables for as long as possible;

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Rankings and Preferences

series data and describe some theoretical results on the weighted correlation coefficients in separate sections.;

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Advances in Classification and Data Analysis

for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a;

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Econometric Analysis of Health Data

limited dependent variables aeo Classical and simulation methods for panel data aeo Publication marks the tenth anniversary of the Workshop series;

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Studies in Theoretical and Applied Statistics

), held in Salerno on 8-10 June 2016. Covering a wide variety of topics ranging from modern data sources and survey design issues to measuring;

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Practical Time Series Analysis

. What You Will Learn * Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science;

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Statistical Inference in Science

A treatment of the problems of inference associated with experiments in science, with the emphasis on techniques for dividing the sample;

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Statistical Inference in Science

A treatment of the problems of inference associated with experiments in science, with the emphasis on techniques for dividing the sample;

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Data Visualization

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction;

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Data Visualization

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction;

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Hands-On Exploratory Data Analysis with Python

fundamental concepts of exploratory data analysis using Python Find missing values in your data and identify the correlation between different;

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Exploratory Causal Analysis with Time Series Data

and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal;

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Random Fields for Spatial Data Modeling

analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the;

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Advances in Disordered Systems, Random Processes and Some Applications

This book offers a unified perspective on the study of complex systems for scholars of various disciplines, including mathematics, physics;

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