Nonparametric Prediction Intervals

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ISBN 13 :
Total Pages : 226 pages
Book Rating : 4.:/5 (34 download)

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Book Synopsis Nonparametric Prediction Intervals by : Lan Chou

Download or read book Nonparametric Prediction Intervals written by Lan Chou and published by . This book was released on 1997 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Prediction Intervals for Sample Medians in the General Case

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Publisher :
ISBN 13 : 9789174740332
Total Pages : 26 pages
Book Rating : 4.7/5 (43 download)

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Book Synopsis Nonparametric Prediction Intervals for Sample Medians in the General Case by : Olivier Guilbaud

Download or read book Nonparametric Prediction Intervals for Sample Medians in the General Case written by Olivier Guilbaud and published by . This book was released on 1981 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Nonparametric approach to the construction of prediction intervals for time series forecasts.Working Paper No.63

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Publisher :
ISBN 13 :
Total Pages : 14 pages
Book Rating : 4.L/5 ( download)

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Book Synopsis A Nonparametric approach to the construction of prediction intervals for time series forecasts.Working Paper No.63 by : W.Allen Spivey and William W. Wecker

Download or read book A Nonparametric approach to the construction of prediction intervals for time series forecasts.Working Paper No.63 written by W.Allen Spivey and William W. Wecker and published by . This book was released on 1972 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Three essays on nonparametric prediction intervals and robust variable selection

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Three essays on nonparametric prediction intervals and robust variable selection by : Marie-Hélène Roy

Download or read book Three essays on nonparametric prediction intervals and robust variable selection written by Marie-Hélène Roy and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Improving Coverage Accuracy of Nonparametric Prediction Intervals

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Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (249 download)

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Book Synopsis Improving Coverage Accuracy of Nonparametric Prediction Intervals by : Peter Hall

Download or read book Improving Coverage Accuracy of Nonparametric Prediction Intervals written by Peter Hall and published by . This book was released on 2001 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Nonparametric Approach to the Construction of Prediction Intervals for Time Series Forecasts

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis A Nonparametric Approach to the Construction of Prediction Intervals for Time Series Forecasts by : W. Allen Spivey

Download or read book A Nonparametric Approach to the Construction of Prediction Intervals for Time Series Forecasts written by W. Allen Spivey and published by . This book was released on 1972 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Intervals

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Publisher : John Wiley & Sons
ISBN 13 : 0471687170
Total Pages : 648 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis Statistical Intervals by : William Q. Meeker

Download or read book Statistical Intervals written by William Q. Meeker and published by John Wiley & Sons. This book was released on 2017-04-10 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

A Non-parametric Approach for Constructing Prediction Intervals for Monotone Functions

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Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis A Non-parametric Approach for Constructing Prediction Intervals for Monotone Functions by : International Business Machines Corporation. Research Division

Download or read book A Non-parametric Approach for Constructing Prediction Intervals for Monotone Functions written by International Business Machines Corporation. Research Division and published by . This book was released on 1989 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Regression Analysis of Longitudinal Data

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Publisher : Springer Science & Business Media
ISBN 13 : 1461239265
Total Pages : 208 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Nonparametric Regression Analysis of Longitudinal Data by : Hans-Georg Müller

Download or read book Nonparametric Regression Analysis of Longitudinal Data written by Hans-Georg Müller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph reviews some of the work that has been done for longitudi nal data in the rapidly expanding field of nonparametric regression. The aim is to give the reader an impression of the basic mathematical tools that have been applied, and also to provide intuition about the methods and applications. Applications to the analysis of longitudinal studies are emphasized to encourage the non-specialist and applied statistician to try these methods out. To facilitate this, FORTRAN programs are provided which carry out some of the procedures described in the text. The emphasis of most research work so far has been on the theoretical aspects of nonparametric regression. It is my hope that these techniques will gain a firm place in the repertoire of applied statisticians who realize the large potential for convincing applications and the need to use these techniques concurrently with parametric regression. This text evolved during a set of lectures given by the author at the Division of Statistics at the University of California, Davis in Fall 1986 and is based on the author's Habilitationsschrift submitted to the University of Marburg in Spring 1985 as well as on published and unpublished work. Completeness is not attempted, neither in the text nor in the references. The following persons have been particularly generous in sharing research or giving advice: Th. Gasser, P. Ihm, Y. P. Mack, V. Mammi tzsch, G . G. Roussas, U. Stadtmuller, W. Stute and R.

Statistical Intervals

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Publisher : John Wiley & Sons
ISBN 13 : 0470317442
Total Pages : 423 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Statistical Intervals by : Gerald J. Hahn

Download or read book Statistical Intervals written by Gerald J. Hahn and published by John Wiley & Sons. This book was released on 2011-09-28 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

EnvStats

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Publisher : Springer Science & Business Media
ISBN 13 : 1461484561
Total Pages : 305 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis EnvStats by : Steven P. Millard

Download or read book EnvStats written by Steven P. Millard and published by Springer Science & Business Media. This book was released on 2013-10-16 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analyses of environmental data, bringing major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. EnvStats also includes numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. This book shows how to use EnvStats and R to easily: * graphically display environmental data * plot probability distributions * estimate distribution parameters and construct confidence intervals on the original scale for commonly used distributions such as the lognormal and gamma, as well as do this nonparametrically * estimate and construct confidence intervals for distribution percentiles or do this nonparametrically (e.g., to compare to an environmental protection standard) * perform and plot the results of goodness-of-fit tests * compute optimal Box-Cox data transformations * compute prediction limits and simultaneous prediction limits (e.g., to assess compliance at multiple sites for multiple constituents) * perform nonparametric estimation and test for seasonal trend (even in the presence of correlated observations) * perform power and sample size computations and create companion plots for sampling designs based on confidence intervals, hypothesis tests, prediction intervals, and tolerance intervals * deal with non-detect (censored) data * perform Monte Carlo simulation and probabilistic risk assessment * reproduce specific examples in EPA guidance documents EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”

Model-Free Prediction and Regression

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ISBN 13 : 9783319213484
Total Pages : pages
Book Rating : 4.2/5 (134 download)

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Book Synopsis Model-Free Prediction and Regression by : Dimitris N. Politis

Download or read book Model-Free Prediction and Regression written by Dimitris N. Politis and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality. Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, computer-intensive methods such as the bootstrap and cross-validation freed practitioners from the limitations of parametric models, and paved the way towards the `big data' era of the 21st century. Nonetheless, there is a further step one may take, i.e., going beyond even nonparametric models; this is where the Model-Free Prediction Principle is useful. Interestingly, being able to predict a response variable Y associated with a regressor variable X taking on any possible value seems to inadvertently also achieve the main goal of modeling, i.e., trying to describe how Y depends on X. Hence, as prediction can be treated as a by-product of model-fitting, key estimation problems can be addressed as a by-product of being able to perform prediction. In other words, a practitioner can use Model-Free Prediction ideas in order to additionally obtain point estimates and confidence intervals for relevant parameters leading to an alternative, transformation-based approach to statistical inference.

Statistical Methods for Machine Learning

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Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 291 pages
Book Rating : 4./5 ( download)

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Book Synopsis Statistical Methods for Machine Learning by : Jason Brownlee

Download or read book Statistical Methods for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-05-30 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.

Statistical Methods in Water Resources

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Publisher : Elsevier
ISBN 13 : 0080875084
Total Pages : 539 pages
Book Rating : 4.0/5 (88 download)

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Book Synopsis Statistical Methods in Water Resources by : D.R. Helsel

Download or read book Statistical Methods in Water Resources written by D.R. Helsel and published by Elsevier. This book was released on 1993-03-03 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources. The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies. The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.

Parametric and Nonparametric Inference from Record-Breaking Data

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Publisher : Springer Science & Business Media
ISBN 13 : 0387215492
Total Pages : 123 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Parametric and Nonparametric Inference from Record-Breaking Data by : Sneh Gulati

Download or read book Parametric and Nonparametric Inference from Record-Breaking Data written by Sneh Gulati and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.

Expected Coverage of Prediction Intervals in a Two-parameter Non-linear Model

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis Expected Coverage of Prediction Intervals in a Two-parameter Non-linear Model by : A. H. Pooi

Download or read book Expected Coverage of Prediction Intervals in a Two-parameter Non-linear Model written by A. H. Pooi and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data Analysis with Small Samples and Non-normal Data

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Publisher : Oxford University Press
ISBN 13 : 0199391491
Total Pages : 241 pages
Book Rating : 4.1/5 (993 download)

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Book Synopsis Data Analysis with Small Samples and Non-normal Data by : Carl F. Siebert

Download or read book Data Analysis with Small Samples and Non-normal Data written by Carl F. Siebert and published by Oxford University Press. This book was released on 2018 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to nonparametrics -- Analyzing single variables and single groups -- Comparing two or more independent groups -- Comparing two or more related groups -- Predicting with multiple independent variables -- Appendix -- Index