Handbook of Quantile Regression, Koenker, Roger

Автор: Uribe Jorge M., Guillen Montserrat
Название: Quantile Regression for Cross-Sectional and Time Series Data: Applications in Energy Markets Using R
ISBN: 3030445038 ISBN-13(EAN): 9783030445034
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables.

Автор: Cleophas Ton J., Zwinderman Aeilko H.
Название: Quantile Regression in Clinical Research: Complete Analysis for Data at a Loss of Homogeneity
ISBN: 3030828395 ISBN-13(EAN): 9783030828394
Издательство: Springer
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Цена: 60550.00 T
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Описание: Quantile regression is an approach to data at a loss of homogeneity, for example (1) data with outliers, (2) skewed data like corona - deaths data, (3) data with inconstant variability, (4) big data. Step by step analyses of over 20 data files stored at extras.springer.com are included for self-assessment.

Автор: Koenker
Название: Quantile Regression
ISBN: 0521845734 ISBN-13(EAN): 9780521845731
Издательство: Cambridge Academ
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Цена: 104550.00 T
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Описание: Quantiles provide a natural description of statistical variability in diverse populations; quantile regression offers a unified statistical methodology for studying how these measures of diversity depend upon other influences.

Автор: Davino Cristina
Название: Quantile Regression
ISBN: 111997528X ISBN-13(EAN): 9781119975281
Издательство: Wiley
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Цена: 77030.00 T
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Описание: A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods.

Автор: Koenker, Roger
Название: Quantile regression
ISBN: 0521608279 ISBN-13(EAN): 9780521608275
Издательство: Cambridge Academ
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Цена: 40120.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Quantiles provide a natural description of statistical variability in diverse populations; quantile regression offers a unified statistical methodology for studying how these measures of diversity depend upon other influences.

Автор: Bernd Fitzenberger; Roger Koenker; Jose A.F. Macha
Название: Economic Applications of Quantile Regression
ISBN: 3790825026 ISBN-13(EAN): 9783790825022
Издательство: Springer
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Цена: 163040.00 T
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Описание: Complementing classical least squares regression methods which are designed to estimate conditional mean models, quantile regression provides an ensemble of techniques for estimating families of conditional quantile models, thus offering a more complete view of the stochastic relationship among variables.

Автор: N. Unnikrishnan Nair; P.G. Sankaran; N. Balakrishn
Название: Quantile-Based Reliability Analysis
ISBN: 149395167X ISBN-13(EAN): 9781493951673
Издательство: Springer
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Цена: 55850.00 T
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Описание: This book provides a fresh approach to reliability theory, an area that has gained increasing relevance in fields from statistics and engineering to demography and insurance. Its innovative use of quantile functions gives an analysis of lifetime data that is generally simpler, more robust, and more accurate than the traditional methods, and opens the door for further research in a wide variety of fields involving statistical analysis. In addition, the book can be used to good effect in the classroom as a text for advanced undergraduate and graduate courses in Reliability and Statistics.

Автор: Gilchrist, Warren
Название: Statistical Modelling with Quantile Functions
ISBN: 0367398680 ISBN-13(EAN): 9780367398682
Издательство: Taylor&Francis
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Цена: 65320.00 T
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Описание:

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.

Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.

Statistical Modelling with Quantile Functions adds a new dimension to the practice of statistical modelling that will be of value to anyone faced with analyzing data. Not intended to replace classical approaches but to supplement them, it will make some of the traditional topics easier and clearer, and help readers build and investigate models for their own practical statistical problems.

Автор: Gilchrist, Warren
Название: Statistical Modelling with Quantile Functions
ISBN: 1584881747 ISBN-13(EAN): 9781584881742
Издательство: Taylor&Francis
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Цена: 148010.00 T
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Название: Sage handbook of regression analysis and causal inference
ISBN: 1446252442 ISBN-13(EAN): 9781446252444
Издательство: Sage Publications
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Цена: 142560.00 T
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Автор: Paulson, Daryl S.
Название: Handbook of Regression and Modeling
ISBN: 1032477857 ISBN-13(EAN): 9781032477855
Издательство: Taylor&Francis
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Цена: 46950.00 T
Наличие на складе: Нет в наличии.

Автор: Mcnulty, Keith
Название: Handbook of regression modeling in people analytics
ISBN: 1032041749 ISBN-13(EAN): 9781032041742
Издательство: Taylor&Francis
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Цена: 68390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling.