Statistical data analysis based on the L₁-norm and related methods
Read Online
Share

Statistical data analysis based on the L₁-norm and related methods by International Conference on the Lв‚Ѓ-norm and Related Methods (4th 2002 NeuchaМ‚tel, Switzerland)

  • 737 Want to read
  • ·
  • 76 Currently reading

Published by Birkhäuser in Boston .
Written in English

Subjects:

  • Least absolute deviations (Statistics) -- Congresses.,
  • Mathematical statistics -- Congresses.

Book details:

Edition Notes

Includes bibliographical references.

StatementYadolah Dodge, editor ; Giuseppe Melfi, technical assistant.
GenreCongresses.
SeriesStatistics for industry and technology
ContributionsDodge, Yadolah, 1944-
Classifications
LC ClassificationsQA275 .I47 2002, QA275 .I47 2002
The Physical Object
Paginationxii, 454 p. :
Number of Pages454
ID Numbers
Open LibraryOL18176184M
ISBN 100817669205, 3764369205
LC Control Number2002026036

Download Statistical data analysis based on the L₁-norm and related methods

PDF EPUB FB2 MOBI RTF

Summary This book contains the invited papers presented at the First International Conference on Statistical Data Analysis based on the L 1 -Norm and Related Methods, held in Neuchatel . "Papers prepared at the First International Conference on Statistical Data Analysis Based on the L₁-norm and Related Methods, held in Neuchâtel, Switzerland, from August September 4, "- . Contains papers presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in Papers show the importance of development of theory, methods and applications related to statistical data analysis based on . This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in NeuchA[tel, Switzerland, from August 4a "9, The contributions represent a clear evidence to the importance of development of theory, methods and applications related to the statistical data analysis based on.

STATISTICAL DATA ANALYSIS BASED ON THE L1-NORM AND RELATED METHODS by Yadolah Dodge (Editor) The volume is a selection of papers, presented to the fourth International Conference on Statistical Analysis Based on the L1-Norm and Related Meth-ods, held in Neuchatel, Switzerland in The theory and applications of statistical methods based on L1-norm are a promising fields of statistics. This book presents a combination of individual topics with solved problems and a collection of experimental tasks. Methods suitable for extreme or small and large datasets are described. Show less. Over the past decade, computer supported data analysis by statistical methods . Quantitative Analysis. Mathematics Fundamentals. Applied Business Analysis. A Handbook of Statistics. Introduction to Vectors. Decision-Making using Financial Ratios. Statistics for Business and Economics. Understanding Statistics. An Introduction to Matlab. A Refresher Course in Mathematics. Introduction to statistical data analysis . Exploratory Data Analysis 8 Randomness and Randomization Random numbers Random permutations Resampling Runs test Random walks Markov processes Monte Carlo methods File Size: 1MB.

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis . The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques, statistical tests, and methods of parameter estimation. The last three chapters then develop more advanced statistical ideas Cited by: and the input data, one can gain experience with the methods presented. This is particularly instructive in conjunction with the Monte Carlo method (Chapter 3), which allows one to generate simulated data sets with known properties. These can then be used as input to test the various statistical .