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Multivariate Frequency Analysis of Hydro-Meteorological Variables

Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach provides comprehensive and detailed;

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Statistical Analysis of Hydrologic Variables

Environmental and Water Resources Institute. Statistical Analysis of Hydrologic Variables: Methods and Applications provides a compilation of state;

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Advances in Hydro-Meteorological Monitoring

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Exploratory Multivariate Analysis by Example Using R

) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and;

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Exploratory Multivariate Analysis by Example Using R

) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and;

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Predictive Hydrology

The unusual frequency of hydro-meteorological events in recent decades, often with catastrophic consequences for society and the;

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Copulas and their Applications in Water Resources Engineering

multivariate and their treatment requires multivariate frequency analysis. Traditional analysis methods are, however, too restrictive and do not apply;

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Econometrics of Financial High-frequency Data

conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic;

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Hydro-Meteorological Hazards Risks & Dis

Hydro-Meteorological Hazards, Risks, and Disasters provides an integrated look at major atmospheric disasters that have had and;

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A Primer of Multivariate Statistics

importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.;

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A Primer of Multivariate Statistics

importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.;

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Temporal Water Quality Trends in Lake Ziway (Ethiopia)

variation in the hydro-meteorological factors that determine the chemical characteristics of the lake. It succinctly depicts the causal;

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Multivariate Statistical Methods

variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical;

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Multivariate Statistical Methods

variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical;

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Multivariate Statistics

The authors have cleverly used exercises and their solutions to explore the concepts of multivariate data analysis. Broken down into three;

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Copulas and Its Application in Hydrology and Water Resources

or multivariate models. The specific applications covered include the study of flood frequency analysis, drought frequency analysis;

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Climate And Hydrology Of Mountain Areas

Change, Snow Melt and Soil Water, Run--off and Floods, Water fluxes and Water Balance, Hydro--meteorological Coupling and Modelling. Each section;

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Global Satellite Meteorological Observation (GSMO) Applications

measurements of meteorological variables, atmosphere and surface applications, ocean and coastal applications, land, agriculture and forestry;

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Multivariate Statistics

The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted;

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Introduction to Multivariate Analysis

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling;

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Introduction to Multivariate Analysis

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows;

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Applied Multivariate Data Analysis

Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables;

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Systems of Frequency Distributions for Water and Environmental Engineering

by random variables. These variables are described by frequency distributions. This book provides an overview of different systems;

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Intelligent Data Analytics for Decision Support Systems in Hazard Mitigation

forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards;

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Intelligent Data Analytics for Decision Support Systems in Hazard Mitigation

forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards;

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Analysis of Multivariate Survival Data

, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing;

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Semantic Kriging for Spatio-temporal Prediction

This book identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy of meteorological;

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