3 edition of **Algorithms, Routines and S Functions for Robust Statistics** found in the catalog.

Algorithms, Routines and S Functions for Robust Statistics

Alfio Marazzi

- 126 Want to read
- 30 Currently reading

Published
**1993**
by Wadsworth & Brooks/ColesfLondon, Chapman & Hall [distributor] in Pacific Grove, Cal
.

Written in English

- ROBETH.,
- Robust statistics -- Data processing.

**Edition Notes**

International student ed.

Statement | Alfio Marazzi with the collaboration of Johann Joss, Alex Randriamiharisoa. |

Series | Wadsworth & Brooks/Cole statistics/probability series |

Contributions | Joss, Johann., Randriamiharisoa, Alex. |

The Physical Object | |
---|---|

Pagination | xii,436p. ; |

Number of Pages | 436 |

ID Numbers | |

Open Library | OL21513059M |

ISBN 10 | 0534196985 |

Computational Statistics & Data Analysis 19 () North-Holland Recursive robust regression computational aspects and comparison Jaromir Antoch Charles University, Prague, Czech Republic Hakan Ekblom Lulea University, Lule Sweden Received November Revised May Abstract: The main objective of this paper is to show how algorithms for classical robust Cited by: concepts and algorithms. The algorithm engineering approach has been successfully applied to many problems and often achieved impressive speed-ups (as in routing algorithms, see, e.g. [DSSW09] and the book [MHS10]). Even though this aspect has not been su ciently acknowledged in the robust opti-.

Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not statistical methods have been developed for many common problems, such as estimating location, scale, and regression motivation is to produce statistical methods that are not unduly . Algorithms Routines And S Functions For Robust Statistics Author: Alfio Marazzi ISBN:

Documentation in Algorithms, Routines and S Functions for Robust Statistics, book by Marazzi (, Wadsworth and Brooks/Cole) [email protected] at a "modest price" . Functions related to robust estimation have been added to: Mathematical Functions/Statistics/Robust Statistics/ One can, for example, fit lines to data corrupted with arbitrary bad measurements. Added many more combinatoric functions and updated existing ones. See Mathematical Functions/Combinatorics/.

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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 by: 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. Algorithms, Routines, and S-Functions for Robust Statistics - CRC Press Book 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 book.

Robust procedures are needed to give stable results when outliers are present. This book gives all the details for hundreds of routines, described in FORTRAN notation.

The authors assume that the user can interface these routines. (). Algorithms, Routines, and S Functions, for Robust Statistics. Technometrics: Vol. 37, No. 3, pp. Author: Boris Iglewicz, Richard M. Heiberger, Dirk Moore, Yun Tan. Buy Algorithms, Routines, and S-Functions for Robust Statistics by Alfio Marazzi from Waterstones today.

Click and Collect from your local Waterstones or get FREE UK delivery on orders over £Author: Alfio Marazzi. Algorithms, routines, and S functions for robust statistics: the FORTRAN library ROBETH with an interface to S-PLUS Wadsworth Publ.

Belmont, CA, USA © ISBNCited by: Robust Statistics aims to stimulate the use of robust methods as a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. It is an ideal resource for researchers, practitioners, and graduate students in statistics, engineering, computer science, and physical and social sciences.

new books on Robust Statistics The package robustbase robustbase: current status overview rrcov \Functions for Robust Location and Scatter Valentin's routines use the fast algorithms of Peter Rousseeuw and Katrien van Driessen ().

Bounded-influence estimation is a well developed and useful theory. It provides fairly efficient estimators which are robust to outliers and local model departures. However, its use has been limited thus far, mainly because of computational by: 5.

Algorithms, routines, and S functions for robust statistics: the FORTRAN library ROBETH with an interface to S-PLUS Responsibility Alfio Marazzi with the collaboration of Johann Joss, Alex Randriamiharisoa. Algorithms, routines and S functions for robust statistics: the FORTRAN library ROBETH with an interface to S-PLUS: 1.

Selected numerical algorithms for computing robust estimates and convergence proofs are provided throughout the book, along with quantitative robustness information for a variety of estimates. A General Remarks section appears at the beginning of each chapter 5/5(3).

Part of the Springer Handbooks of Computational Statistics book series (SHCS) The first example involves the real data given in Table which are the results of an interlaboratory test. The boxplots are shown in Fig. where the dotted line denotes the mean of the observations and the solid line the median.

Asymptotically, a τ estimate is equivalent to an M estimate with a ψ function given by a weighted average of two ψ functions, one corresponding to a very robust estimate and the other to a. The EM algorithm from statistics is a special case.

An MM algorithm operates by creating a surrogate function that minorizes or majorizes the objective function. When the surrogate function is optimized, the objective function is driven uphill or downhill as Size: KB. Algorithms, routines, and S functions for robust statistics: the FORTRAN library ROBETH with an interface to S-PLUS Author: Alfio Marazzi ; Johann Joss ; Alex Randriamiharisoa.

Algorithms, routines, and S functions for robust statistics. The FORTRAN library ROBETH with an interface to S-PLUS. With the collaboration of Johann Joss and Alex RandriamiharisoaAuthor: Murray Jorgensen. To compute least absolute residuals (LAR) or “L1” regression, implements the routine L1 in Barrodale and Roberts (), which is based on the simplex method of linear programming.

It is a copy of (in early ) from the robust package. ROBETH is the program library for robust statistical procedures described in the book entitled "Algorithms, Routines and S-Plus Functions" by A. Marazzi (Wadsworth and Brooks/Cole, ; reprinted by Chapman Hall). ROBETH has been interfaced to the statistical environments S.

In this post “Important top 10 algorithms and data structures for competitive coding “. Graph algorithms. Dynamic programming. Searching and Sorting: Number theory and Other Mathematical.

Geometrical and Network Flow Algorithms. Data Structures. The below links cover all most important algorithms and data structure topics: Graph Algorithms/5.In this article, I introduce robust routines and a procedure in SAS.

The routines are in SAS/IML, acting as function calls. They are LTS, LMS, MCD, MVE, LAV, and MAD. These routines have been released in SAS/IML V or in previous versions. The SAS/STAT procedure, ROBUSTREG, is : C. Chen.In robustbase: Basic Robust Statistics. Description Usage Arguments Details Value Author(s) References See Also Examples.

Description. To compute least absolute residuals (LAR) or “L1” regression, implements the routine L1 in Barrodale and Roberts (), which is based on the simplex method of linear programming. It is a copy of (in early ) from the robust .