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Statistical Modeling and Data Analysis, 


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Название:  Statistical Modeling and Data Analysis
ISBN: 9781466557758
Издательство: Taylor&Francis
Классификация:


ISBN-10: 1466557753
Обложка/Формат: Hardback
Страницы: 400
Вес: 0.00 кг.
Дата издания: 30.03.2025
Серия: Chapman & hall/crc texts in statistical science
Язык: English
Иллюстрации: 75 illustrations, black and white
Размер: 234 x 156
Подзаголовок: An introduction
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз

The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Computer Age Statistical Inference, Student Edition

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
Рейтинг:
Цена: 33790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Excel data analysis

Автор: Guerrero, Hector
Название: Excel data analysis
ISBN: 3030012786 ISBN-13(EAN): 9783030012786
Издательство: Springer
Рейтинг:
Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive and readable introduction to modern business and data analytics.

Analysis Of Variance, Design & Regr

Автор: Christensen
Название: Analysis Of Variance, Design & Regr
ISBN: 1498730140 ISBN-13(EAN): 9781498730143
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.

New to the Second Edition

  • Reorganized to focus on unbalanced data
  • Reworked balanced analyses using methods for unbalanced data
  • Introductions to nonparametric and lasso regression
  • Introductions to general additive and generalized additive models
  • Examination of homologous factors
  • Unbalanced split plot analyses
  • Extensions to generalized linear models
  • R, Minitab(R), and SAS code on the author's website

The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.


Statistical & Machine-Learning Data

Автор: Ratner
Название: Statistical & Machine-Learning Data
ISBN: 1498797601 ISBN-13(EAN): 9781498797603
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining.

Multivariate Statistical Modeling and Data Analysis

Автор: H. Bozdogan; Arjun K. Gupta
Название: Multivariate Statistical Modeling and Data Analysis
ISBN: 9027725926 ISBN-13(EAN): 9789027725929
Издательство: Springer
Рейтинг:
Цена: 136910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor- relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.

Statistical Modeling, Analysis and Management of Fuzzy Data

Автор: Carlo Bertoluzza; Maria A. Gil; Dan A. Ralescu
Название: Statistical Modeling, Analysis and Management of Fuzzy Data
ISBN: 3790825018 ISBN-13(EAN): 9783790825015
Издательство: Springer
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Цена: 153720.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.

Statistical Modeling and Analysis for Complex Data Problems

Автор: Pierre Duchesne; Bruno R?millard
Название: Statistical Modeling and Analysis for Complex Data Problems
ISBN: 144193751X ISBN-13(EAN): 9781441937513
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors - largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes - present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.


Multivariate Statistical Modeling and Data Analysis

Автор: H. Bozdogan; Arjun K. Gupta
Название: Multivariate Statistical Modeling and Data Analysis
ISBN: 9401082642 ISBN-13(EAN): 9789401082648
Издательство: Springer
Рейтинг:
Цена: 136910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor- relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.

Dynamic Data Analysis

Автор: James Ramsay; Giles Hooker
Название: Dynamic Data Analysis
ISBN: 1493984128 ISBN-13(EAN): 9781493984121
Издательство: Springer
Рейтинг:
Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Introduction to Dynamic Models

1.1 Six Examples of Input/Output Dynamics

1.1.1 Smallpox in Montreal

1.1.2 Spread of Disease Equations

1.1.3 Filling a Container

1.1.4 Head Impact and Brain Acceleration

1.1.5 Compartment models and pharmacokinetics

1.1.6 Chinese handwriting

1.1.7 Where to go for More Dynamical Systems

1.2 What This Book Undertakes

1.3 Mathematical Requirements

1.4 Overview

2 DE notation and types

2.1 Introduction and Chapter Overview

2.2 Notation for Dynamical Systems

2.2.1 Dynamical System Variables

2.2.2 Dynamical System Parameters

2.2.3 Dynamical System Data Configurations

2.2.4 Mathematical Background

2.3 The Architecture of Dynamic Systems

2.4 Types of Differential Equations

2.4.1 Linear Differential Equations

2.4.2 Nonlinear Dynamical Systems

2.4.3 Partial Differential Equations

2.4.4 Algebraic and Other Equations

2.5 Data Configurations

2.5.1 Initial and Boundary Value Configurations

2.5.2 Distributed Data Configurations

2.5.3 Unobserved or Lightly Observed Variables

2.5.4 Observational Data and Measurement Models

2.6 Differential Equation Transformations

2.7 A Notation Glossary

3 Linear Differential Equations and Systems

3.1 Introduction and Chapter Overview

3.2 The First Order Stationary Linear Buffer

3.3 The Second Order Stationary Linear Equation

3.4 The mth Order Stationary Linear Buffer

3.5 Systems of Linear Stationary Equations

3.6 A Linear System Example: Feedback Control

3.7 Nonstationary Linear Equations and Systems

3.7.1 The First Order Nonstationary Linear Buffer

3.7.2 First Order Nonstationary Linear Systems

3.8 Linear Differential Equations Corresponding to Sets of Functions

3.9 Green's Functions for Forcing Function Inputs

4 Nonlinear Differential Equations

4.1 Introduction and Chapter Overview

4.2 The Soft Landing Modification

4.3 Existence and Uniqueness Results

4.4 Higher Order Equations

4.5 Input/Output Systems

4.6 Case Studies

4.6.1 Bounded Variation: The Catalytic Equation

4.6.2 Rate Forcing: The SIR Spread of Disease System

4.6.3 From Linear to Nonlinear: The FitzHugh-Nagumo Equations

4.6.4 Nonlinear Mutual Forcing: The Tank Reactor Equations

4.6.5 Modeling Nylon Production

5 Numerical Solutions

5.1 Introduction

5.2 Euler Methods

5.3 Runge-KuttaMethods

5.4 Collocation Methods

5.5 Numerical Problems

5.5.1 Stiffness

5.5.2 Discontinuous Inputs

5.5.3 Constraints and Transformations

6 Qualitative Behavior

6.1 Introduction

6.2 Fixed Points

6.2.1 Stability

6.3 Global Analysis and Limit Cycles

6.3.1 Use of Conservation Laws

6.3.2 Bounding Boxes

6.4 Bifurcations

6.4.1 Transcritical Bifurcations

6.4.2 Saddle Node Bifurcations

6.4.3 Pitchfork Bifurcations

6.4.4 Hopf Bifurcations

6.5 Some Other Features

6.5.1 Chaos

6.5.2 Fast-Slow Systems

6.6 Non-autonomous Systems

6.7 Commentary

7 Trajectory Matching

7.1 Introduction

7.2 Gauss-Newton Minimization

7.2.1 Sensitivity Equations

7.2.2 Automatic Differentiation

7.3 Inference

7.4 Measurements on Multiple Variables

7.4.1 Multivariate Gauss-Newton Method

7.4.2 VariableWeighting using Error Variance

7.4.3 Estimating s2

7.4.4 Example: FitzHugh-NagumoModels

7.4.5 Practical Proble

A Practitioner`s  Guide to Resampling for Data Analysis, Data Mining, and Modeling

Автор: Good, Phillip
Название: A Practitioner`s Guide to Resampling for Data Analysis, Data Mining, and Modeling
ISBN: 0367382482 ISBN-13(EAN): 9780367382483
Издательство: Taylor&Francis
Рейтинг:
Цена: 61240.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Distribution-free resampling methods--permutation tests, decision trees, and the bootstrap--are used today in virtually every research area. A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling explains how to use the bootstrap to estimate the precision of sample-based estimates and to determine sample size, data permutations to test hypotheses, and the readily-interpreted decision tree to replace arcane regression methods.

Highlights

  • Each chapter contains dozens of thought provoking questions, along with applicable R and Stata code
  • Methods are illustrated with examples from agriculture, audits, bird migration, clinical trials, epidemiology, image processing, immunology, medicine, microarrays and gene selection
  • Lists of commercially available software for the bootstrap, decision trees, and permutation tests are incorporated in the text
  • Access to APL, MATLAB, and SC code for many of the routines is provided on the author's website
  • The text covers estimation, two-sample and k-sample univariate, and multivariate comparisons of means and variances, sample size determination, categorical data, multiple hypotheses, and model building

Statistics practitioners will find the methods described in the text easy to learn and to apply in a broad range of subject areas from A for Accounting, Agriculture, Anthropology, Aquatic science, Archaeology, Astronomy, and Atmospheric science to V for Virology and Vocational Guidance, and Z for Zoology.

Practitioners and research workers and in the biomedical, engineering and social sciences, as well as advanced students in biology, business, dentistry, medicine, psychology, public health, sociology, and statistics will find an easily-grasped guide to estimation, testing hypotheses and model building.


Statistical Learning and Modeling in Data Analysis: Methods and Applications

Автор: Balzano Simona, Porzio Giovanni C., Salvatore Renato
Название: Statistical Learning and Modeling in Data Analysis: Methods and Applications
ISBN: 3030699439 ISBN-13(EAN): 9783030699437
Издательство: Springer
Цена: 149060.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications.


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