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Probability Methods for Cost Uncertainty Analysis, Garvey, Paul R.


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Цена: 48990.00T
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Автор: Garvey, Paul R.
Название:  Probability Methods for Cost Uncertainty Analysis
ISBN: 9780367737429
Издательство: Taylor&Francis
Классификация:



ISBN-10: 0367737426
Обложка/Формат: Paperback
Страницы: 528
Вес: 0.45 кг.
Дата издания: 18.12.2020
Язык: English
Издание: 2 ed
Размер: 231 x 155 x 31
Читательская аудитория: Tertiary education (us: college)
Подзаголовок: A systems engineering perspective, second edition
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Поставляется из: Европейский союз

Dicing with death

Автор: Senn, Stephen
Название: Dicing with death
ISBN: 1108999867 ISBN-13(EAN): 9781108999861
Издательство: Cambridge Academ
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Цена: 21110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From measles to malaria, from clinical trials to COVID and from life tables to the law, the second edition of Dicing with Death explains how the vital decisions we have to make both individually and collectively can be informed and improved by good data, statistical reasoning and analysis.

All the Math You Missed

Автор: Thomas A. Garrity
Название: All the Math You Missed
ISBN: 1009009192 ISBN-13(EAN): 9781009009195
Издательство: Cambridge Academ
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Цена: 26400.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The second edition of this bestselling book provides an overview of the key topics in undergraduate mathematics, allowing beginning graduate students to fill in any gaps in their knowledge. With numerous examples, exercises and suggestions for further reading, it is a must-have for anyone looking to learn some serious mathematics quickly.

Mathematics for Machine Learning

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
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Цена: 42230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Growth Curve Analysis and Visualization Using R

Автор: Mirman
Название: Growth Curve Analysis and Visualization Using R
ISBN: 1466584327 ISBN-13(EAN): 9781466584327
Издательство: Taylor&Francis
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Цена: 91860.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data. It also provides a way to quantify and analyze individual differences, such as developmental and neuropsychological, in the context of a model of the overall group effects. To harness the practical aspects of this useful tool, behavioral science researchers need a concise, accessible resource that explains how to implement these analysis methods. Growth Curve Analysis and Visualization Using R provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. The book begins with discussing problems encountered when analyzing time course data, how to visualize time course data using the ggplot2 package, and how to format data for GCA and plotting. It then presents a conceptual overview of GCA and the core analysis syntax using the lme4 package and demonstrates how to plot model fits. The book describes how to deal with change over time that is not linear, how to structure random effects, how GCA and regression use categorical predictors, and how to conduct multiple simultaneous comparisons among different levels of a factor. It also compares the advantages and disadvantages of approaches to implementing logistic and quasi-logistic GCA and discusses how to use GCA to analyze individual differences as both fixed and random effects. The final chapter presents the code for all of the key examples along with samples demonstrating how to report GCA results. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. Each chapter ends with exercises to test your understanding. The example datasets, code for solutions to the exercises, and supplemental code and examples are available on the author’s website.

The Fence Methods

Автор: Jiang Jiming, Nguyen Thuan
Название: The Fence Methods
ISBN: 981459606X ISBN-13(EAN): 9789814596060
Издательство: World Scientific Publishing
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Цена: 84480.00 T
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Описание:

This book is about a recently developed class of strategies, known as the fence methods, which fits particularly well in non-conventional and complex model selection problems with practical considerations. The idea involves a procedure to isolate a subgroup of what are known as correct models, of which the optimal model is a member. This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from amongst those within the fence according to a criterion which can be made flexible. In particular, the criterion of optimality can incorporate consideration of practical interest, thus making model selection a real life practice.

Furthermore, this book introduces a data-driven approach, called adaptive fence, which can be used in a wide range of problems involving determination of tuning parameters, or constants. Instead of relying on asymptotic theory, the fence focuses on finite-sample performance, and computation. Such features are particularly suitable to statistics in the new era.


State-Space Methods for Time Series Analysis

Автор: Casals Jose Manuel Carro
Название: State-Space Methods for Time Series Analysis
ISBN: 148221959X ISBN-13(EAN): 9781482219593
Издательство: Taylor&Francis
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Цена: 102080.00 T
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Описание:

The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values.

Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form.

After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables.

Web Resource
The authors' E4 MATLAB(R) toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.


Complex Survey Data Analysis with SAS

Автор: Lewis
Название: Complex Survey Data Analysis with SAS
ISBN: 1498776779 ISBN-13(EAN): 9781498776776
Издательство: Taylor&Francis
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Цена: 91860.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Complex Survey Data Analysis with SAS (R) is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors.

Textual Statistics with R

Автор: Becue-Bertaut
Название: Textual Statistics with R
ISBN: 1138626910 ISBN-13(EAN): 9781138626911
Издательство: Taylor&Francis
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Цена: 122490.00 T
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Описание: Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

Handbook of Cluster Analysis

Название: Handbook of Cluster Analysis
ISBN: 1466551887 ISBN-13(EAN): 9781466551886
Издательство: Taylor&Francis
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Цена: 224570.00 T
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Описание:

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.

The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids, dissimilarity-based methods, mixture models and partitioning models, and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis, including constrained and semi-supervised clustering, and explores other relevant issues, such as evaluating the quality of a cluster.

This handbook is accessible to readers from various disciplines, reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis, the book offers a broad and structured overview. For newcomers to the field, it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems, the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.


Uncertainty Analysis for Engineers and Scientists

Автор: Morrison Faith A.
Название: Uncertainty Analysis for Engineers and Scientists
ISBN: 1108478352 ISBN-13(EAN): 9781108478359
Издательство: Cambridge University Press
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Цена: 145910.00 T
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Описание: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Whether you are new to the sciences or an experienced engineer, this useful text provides a practical approach to performing error analysis.

Large-Scale System Analysis Under Uncertainty: With Electric Power Applications

Автор: Domнnguez-Garcнa Alejandro D.
Название: Large-Scale System Analysis Under Uncertainty: With Electric Power Applications
ISBN: 1107192080 ISBN-13(EAN): 9781107192089
Издательство: Cambridge University Press
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Цена: 122460.00 T
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Описание: Provides a comprehensive set of tools and techniques for analyzing the impact of uncertainty on large-scale engineered systems. Showcases applications for real-world problems, in areas such as renewable-based power generation, and microgrids. Essential reading for academic researchers and graduate students.

Ignorance and Uncertainty

Автор: Compte Olivier, Postlewaite Andrew
Название: Ignorance and Uncertainty
ISBN: 1108422020 ISBN-13(EAN): 9781108422024
Издательство: Cambridge Academ
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Цена: 104550.00 T
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Описание: Compte and Postlewaite propose novel methods to incorporate ignorance and uncertainty into economic modeling, without complex mathematics. An accessible text that proposes a constructive critique of the discipline, and that will find a broad audience with readers who build or use economic models, and those just interested in the discipline.


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