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Algorithms, Routines, and s Functions for Robust Statistics: The Fortran Library Robeth With an Interface to S-Plus
  
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Algorithms, Routines, and s Functions for Robust Statistics: The Fortran Library Robeth With an Interface to S-Plus [Hardcover]

Alfio Marazzi (Author), Johann Joss (Author), Alex Randriamiharisoa (Author)


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Hardcover $184.95  
Hardcover, February 1993 --  

Book Description

0534196985 978-0534196981 February 1993
ROBETH (written in ANSI FORTRAN 77) is a systematized collection of algorithms that allows computation of a broad class of procedures based on M- and high-breakdown point estimation, including robust regression, robust testing of linear hypotheses, and robust coveriances.

This book describes the computational procedures included in ROBETH. Each chapter is organized into three parts:
1. An overview of the theoretical background for the statistical and numerical methods
2. A detailed description of the corresponding FORTRAN subroutines and of the numerical algorithms as they are implemented
3. The scripts of several examples concerning the use of ROBETH by means of the S-PLUS interface, including some examples of high-level S functions.
--This text refers to an alternate Hardcover edition.

Product Details

  • Hardcover: 440 pages
  • Publisher: Chapman & Hall (February 1993)
  • Language: English
  • ISBN-10: 0534196985
  • ISBN-13: 978-0534196981
  • Product Dimensions: 9.8 x 6.8 x 1 inches
  • Shipping Weight: 1.6 pounds
  • Amazon Best Sellers Rank: #9,351,714 in Books (See Top 100 in Books)

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Inside This Book (learn more)
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First Sentence:
With the help of a few examples, some of the most important concepts, methods, and procedures of robust statistics are introduced in a short and intuitive way in order to provide a guideline for the procedures made available by ROBETH and its interface to S-PLUS. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
compact storage mode, unscaled covariance matrix, high efficiency regression, high breakdown point estimates, symmetric storage mode, bounded influence estimate, given tolerance for the solution, routine documentation, precision array, step length algorithm, breakdown point regression, unstandardized case, iteration monitoring, storage increment, approximate null distribution, bounded influence regression, special programming features, qualitative covariates, main input parameters, auxiliary routines, cleaning scheme, maximum iteration number, robust testing, resampling algorithm, exhaustive inspection
Key Phrases - Capitalized Phrases (CAPs): (learn more)
M-Estimates of Covariance Matrices, Purpose Let, Method Assume, Under Condition, Method Let, Method Numerical, Method First
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