Quantile Regression in Clinical Research: Complete Analysis for Data at a Loss of Homogeneity, Cleophas Ton J., Zwinderman Aeilko H.
Автор: Koenker, Roger Название: Quantile regression ISBN: 0521608279 ISBN-13(EAN): 9780521608275 Издательство: Cambridge Academ Рейтинг: Цена: 6018.00 р. 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: Davino Cristina Название: Quantile Regression ISBN: 111997528X ISBN-13(EAN): 9781119975281 Издательство: Wiley Рейтинг: Цена: 11555.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: N. Unnikrishnan Nair; P.G. Sankaran; N. Balakrishn Название: Quantile-Based Reliability Analysis ISBN: 149395167X ISBN-13(EAN): 9781493951673 Издательство: Springer Рейтинг: Цена: 8378.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses
The conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where each equation estimation of a regression can give only a single regression function or fitted values variable. As an advanced mean regression analysis, each estimation equation of the mean-regression can be used directly to estimate the conditional quantile regression (QR), which can quickly present the statistical results of a set nine QR(τ)s for τ(tau)s from 0.1 up to 0.9 to predict detail distribution of the response or criterion variable. QR is an important analytical tool in many disciplines such as statistics, econometrics, ecology, healthcare, and engineering.
Quantile Regression: Applications on Experimental and Cross Section Data Using EViews provides examples of statistical results of various QR analyses based on experimental and cross section data of a variety of regression models. The author covers the applications of one-way, two-way, and n-way ANOVA quantile regressions, QRs with multi numerical predictors, heterogeneous QRs, and latent variables QRs, amongst others. Throughout the text, readers learn how to develop the best possible quantile regressions and how to conduct more advanced analysis using methods such as the quantile process, the Wald test, the redundant variables test, residual analysis, the stability test, and the omitted variables test. This rigorous volume:
Describes how QR can provide a more detailed picture of the relationships between independent variables and the quantiles of the criterion variable, by using the least-square regression
Presents the applications of the test for any quantile of any numerical response or -criterion variable
Explores relationship of QR with heterogeneity: how an independent variable affects a dependent variable
Offers expert guidance on forecasting and how to draw the best conclusions from the results obtained
Provides a step-by-step estimation method and guide to enable readers to conduct QR analysis using their own data sets
Includes a detailed comparison of conditional QR and conditional mean regression
Quantile Regression: Applications on Experimental and Cross Section Data Using EViews is a highly useful resource for students and lecturers in statistics, data analysis, econometrics, engineering, ecology, and healthcare, particularly those specializing in regression and quantitative data analysis.
Автор: Koenker Название: Quantile Regression ISBN: 0521845734 ISBN-13(EAN): 9780521845731 Издательство: Cambridge Academ Рейтинг: Цена: 15682.00 р. 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 Рейтинг: Цена: 24456.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Hao Название: Quantile Regression: v. 149 ISBN: 1412926289 ISBN-13(EAN): 9781412926287 Издательство: Sage Publications Рейтинг: Цена: 5859.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Quantile Regression establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literatures exist for each subject matter, the authors explore the natural connections between this increasingly sought-after tool and research topics in the social sciences.
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