3 edition of On the application of extreme-value statistics to command oriented problems found in the catalog.
On the application of extreme-value statistics to command oriented problems
John C. Ashlock
1966 by Jet Propulsion Laboratory, California Institute of Technology in Pasadena .
Written in English
|Statement||[by] John C. Ashlock [and] Sandra M. Lurie.|
|Series||JPL technical report no. 32-1025|
|Contributions||Lurie, Sandra M., joint author., United States. National Aeronautics and Space Administration.|
|LC Classifications||TL3280 .A8|
|The Physical Object|
|Pagination||v, 107 p.|
|Number of Pages||107|
|LC Control Number||79014150|
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Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice.
Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing Cited by: It assumes a knowledge of statistics, but many of the ideas and techniques can be used by a nonstatistician.
As a handbook for XTREMES, it is excellent, and I recommend it highly."-Computing Reviews "The present book is a valuable contribution to the various theoretical and applied problems in the area of extreme value theory a pleasure to read."Cited by: Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice.
Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof.5/5(2). Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice.
Intended for statisticians and non-statisticians alike, the theoretical treatment is. The second lecture introduces certain new statistical tools necessary for the theory, which is developed in the third lecture, first in exact, then in asymptotic form.
The fourth lecture shows a series of practical applications and gives all numerical details for enabling interested readers to apply the method to their own problems.
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Summary: The Extremes Toolkit (extRemes) is designed to facilitate the use of extreme value theory in applications oriented toward weather and climate problems that involve extremes, such as the highest temperature over a fixed time period.
This effort is motivated by the continued use of traditional statistical. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics.
Some parts may also serve as an. not changed, but the areas of application and the computational aspects of statistics have changed. Another important improvement is the introduction of statistical software into the text.
The devel-opment of statistical software packages such as SAS, SPSS, and MINITAB has dramatically changed the application of statistics to real-world problems. STATISTICS 8 CHAPTERS 1 TO 6, SAMPLE MULTIPLE CHOICE QUESTIONS Correct answers are in bold italics.
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Author: Larry J. Kitchens, Larry J.(Larry J. Kitchens) Mathematical Statistics with Applications + Student Solutions. extreme value theory in applications oriented toward weather and climate problems that involve extremes, such as the highest temperature over a ﬁxed time period.
This eﬀort is motivated by the continued use of traditional statistical distributions (normal, lognormal, gamma, ) in situations where extreme value theory is applicable. The computational aspects of the book are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph.
students and academic researchers. This book is also accessible to graduate students starting out in the area of functional statistics." (Fazil A. Aliev, Mathematical Reviews, Issue b).
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general mathematical background for probability and statistics. The mathe-matics in this chapter is prerequisite for the main part of the book, and it is hoped that the reader already has command of the material; otherwise, Chapter 0 can be viewed as providing “just in time” mathematics.
Chapter 0 grew (and is growing) recursively. The Extreme value theorem states that if a function is continuous on a closed interval [a,b], then the function must have a maximum and a minimum on the interval.
This makes sense: when a function is continuous you can draw its graph without lifting the pencil. that book can be covered, and on the other hand, as time went by I tended to include some extra stuﬀ, I felt that it would be helpfull to have typed notes, both for me, and for the students.
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It encourages the application of modern management practices to increase efficiency and effectiveness. $\begingroup$ In R, Extreme value theorem is true only for compact sets (i.e. closed and bounded sets) not on open intervals or open sets. $\endgroup$ – PNDas 16 mins ago add a comment | 1 Answer 1.
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