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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Statistical Regression Modeling with R

of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling;

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Statistical Regression Modeling with R

of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling;

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Statistical Learning from a Regression Perspective

This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable;

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Statistical Modelling in Higher Learning

Statistical Modelling in Higher Learning: The book explains the factors that predict the time taken to complete degree programmes.The book;

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Practical Statistics for Data Scientists

belongs to Statistical machine learning methods that learn from data Unsupervised learning methods for extracting meaning from unlabeled data;

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Training Systems Using Python Statistical Modeling

Python's rich suite of libraries for statistical modeling Implement regression, clustering and train neural networks from scratch Includes real;

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An Introduction to Statistical Learning

cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge;

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An Introduction to Statistical Learning

cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge;

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Multivariate Nonparametric Regression And Visualization

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation;

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Applied Regression Including Computing and Graphics

statistical methods and provides a bona fide user manual for the Arc software. It is an invaluable resource for anyone interested in learning how to;

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Regression Methods for Medical Research

the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are;

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Statistical Regression and Classification: From Linear Models to Machine Learning

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned;

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Distributionally Robust Learning

Many of the modern techniques to solve supervised learning problems suffer from a lack of interpretability and analyzability that do not;

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Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at;

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Advanced R Statistical Programming and Data Models

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation;

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Introductory Statistics with R

the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded;

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Environmental Data Analysis

. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based;

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Environmental Data Analysis

. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based;

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Introductory Regression Analysis

in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles;

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Introductory Regression Analysis

in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles;

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Gaussian Process Regression Analysis for Functional Data

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis;

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Regression: Models, Methods and Applications

, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Statistical Methods for Geographers

A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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