5 edition of **Directions in robust statistics and diagnostics** found in the catalog.

- 124 Want to read
- 7 Currently reading

Published
**1991**
by Springer-Verlag in New York
.

Written in English

- Robust statistics -- Congresses.,
- Mathematical statistics -- Congresses.

**Edition Notes**

Other titles | Diagnostics. |

Statement | Werner Stahel, Sanford Weisberg, editors. |

Series | The IMA volumes in mathematics and its applications ;, v. 33-<34 >, IMA volumes in mathematics and its applications ;, v. 33, etc. |

Contributions | Stahel, Werner., Weisberg, Sanford, 1947-, Institute for Mathematics and its Applications. |

Classifications | |
---|---|

LC Classifications | QA276.A1 D57 1991 |

The Physical Object | |

Pagination | v. <1-2 > : |

ID Numbers | |

Open Library | OL1531662M |

ISBN 10 | 0387975306, 0387975314 |

LC Control Number | 91009205 |

Scientific production and competences > SB - School of Basic Sciences > MATH - Institute of Mathematics > STAP - Chair of Applied Statistics Scientific production and competences > SB - School of Basic Sciences > Mathematics Work produced at EPFL Book chapters Published. Logistic Regression is a popular and effective technique for modeling categorical outcomes as a function of both continuous and categorical variables. The question is: how robust is it? Or: how robust are the common implementations? (note: we are using robust in a more standard English sense of performs well for all inputs, not in the technical statistical sense of immune to deviations from.

Companion and complementary diagnostics (CDx) are no exception, but economic evaluation of CDx can pose a number of challenges. To contextualize these issues, an overview of the different types of economic evaluation and the methods generally employed to evaluate health-care . Book Review Forum O’Loughlin and Fotheringham point out, my book contains a forty-page section about what can go wrong with these assumptions. The con-clusion from this exploration by me and others is that the method is more robust to incorrect assumptions than Goodman’s regression, but the degree of robustness is speciﬁc to the data.

Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along with the relevant regression and positive data analysis techniques. It explains how to use RRSM in experimental designs and regression analysis. The system is robust in its overall configuration, with smooth space-time patterns of daily, seasonal and Solar Cycle variability, but shows a hierarchy of interactions among its sub-systems, yielding apparent unpredictability, space-time irregularity, and turbulence.

You might also like

Centre National des Jeunes Agriculteurs.

Centre National des Jeunes Agriculteurs.

CIM framework experience report for 1996

CIM framework experience report for 1996

Economic phenomena before & after war

Economic phenomena before & after war

Environment, Land Management and Society

Environment, Land Management and Society

vector theory of electricity

vector theory of electricity

The dramatic works of Bayard Taylor.

The dramatic works of Bayard Taylor.

Mahatma Gandhis ideas

Mahatma Gandhis ideas

Fusiliers

Fusiliers

Workplace privacy

Workplace privacy

A two-inch board for M. Prynne to peep thorow

A two-inch board for M. Prynne to peep thorow

Reading Dworkin critically

Reading Dworkin critically

Synchrotron radiation.

Synchrotron radiation.

This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA summer program "Robustness, Diagnostics, Computing and Graphics. This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA summer program Read more.

This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". In robust statistics new procedures which have been derived from theoretical considerations are beginning to find their way into applications.

Diagnostics have been designed to supplement standard methodology with both graphical and non-graphical procedures. Many diagnostics, particularly graphical ones, have been generally included in common computing packages.

Directions in Robust Statistics and Diagnostics. Part 1. (Ima Volumes in Mathematics and Its Applications, Vol 33). Department of Statistics Hill Center, Busch Campus Rutgers, The State University of New Jersey Piscataway NJ Office Hill Center Phone Numbers Office: () Department: () FAX: () E-mail dtyler at stat dot rutgers dot edu.

Tyler D.E. () Some Issues in the Robust Estimation of Multivariate Location and Scatter. In: Directions in Robust Statistics and Diagnostics. The IMA Volumes in Cited by: Weisberg, S & Atkinson, ACSimulated Annealing for the detection of Multiple Outliers using least squares and least median of squares fittin.

in W Stahel & S Weisberg (eds), Directions in Robust Statistics and Diagnostics. Springer-Verlag, New York, NY, pp. Cited by: Directions in Robust Statistics and Diagnostics. Yohai; W.A. Stahel the book continues to describe one- and two-sample problems, the basic development of rank methods in the linear model Author: Murray Jorgensen.

Tutorial to robust statistics Tutorial to robust statistics Rousseeuw, Peter J. University of Ant werp (UIA), Vesaliusl B Edegem, Belgium SUMMARY In this tutorial we first illustrate the effect of outliers on classical statistics such as the sample average.

This motivates the use of robust techniques. For univariate data the sample median is a robust estimator. Directions in Robust Statistics and Diagnostics: Part II, ed. Stahel and S. Weisberg, Springer– Verlag: New York, – “Higher Order Effects in Log–Linear and Log–Nonlinear Models for Contingency Tables With Ordered Categories” (), Applied Statistics, 40, – (with C.–L.

Tsai). This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression.

It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods 4/5(2).

Department of Statistics; A procedure for robust estimation and inference in linear regression Title: A procedure for robust estimation and inference in linear regression: Publication Type: Book Chapter: Year of Publication: Authors: Yohai, VJ, Stahel, WA, Zamar, RH: Book Title: Directions in robust statistics and diagnostics.

in Directions in Robust Statistics and Diagnostics, Part 2, W. Stahel and S. Weisberg eds., IMA Volumes in Mathematics and its Applications, 34, Springer-Verlag, New York (). \Approximating & Learning Unknown Mappings Using Multilayer Feedforward Networks with Bounded Weights," with Halbert White, Proceedings of the International Joint Confer.

Sanford Weisberg is the author of Applied Linear Regression ( avg rating, 24 ratings, 1 review, published ), An R Companion to Applied Regression /5. A Review of Robust Regression and Diagnostic Procedures in Linear Regression. ﬁrst who provided criteria for outlier diagnostics.

Following is the summary review of the most popular : Nethal Jajo. Directions in Robust Statistics and Diagnostics II: Part 2 (The IMA Volumes in Mathematics and Its Applications) by Werner A. Stahel Hardcover.

"Directions in Robust Statistics and Diagnostics (Part II)", put one of the designated cartons in its place with the name of the book, your name and the other information boxes filled out.

This way, when someone is looking for the book, the current owner of the book can always be found. "Directions in Robust Statistics and Diagnostics. His next book, written with Michael Friendly, is Data Visualization: A History of Visual Thinking and Graphic Communication will be published by Harvard University Press in Robust statistics: The approach based on influence functions.

New York, NY: Wiley Weisberg, S. (Eds.), Directions in robust statistics and diagnostics, Author: Arnond Sakworawich, Howard Wainer. Logistic Regression is a popular and effective technique for modeling categorical outcomes as a function of both continuous and categorical variables.

The question is: how robust is it. Or: how robust are the common implementations. (note: we are using robust in a more standard English sense of performs well for all inputs, not in the technical statistical sense of immune to deviations from.

Diagnostics," with Xizhi Wu, Directions in Robust Statistics and Diagnostics, (Part II), Springer-Verlag,pp. "Assessing the Influence of Individual Observations On a Goodness-Of-Fit Test Based On Nonparametric Regression," with Jeffrey S.

Simonoff, Statistics and File Size: 32KB.The Institute for Digital Research and Education (IDRE) has a collection of books on statistics and statistical computing available for UCLA researchers to borrow on a short term basis to help with research.

Many of the books have web pages associated with them that have the data files for the book and web pages showing how to perform the.Downloadable! We develop simple procedures to test for omitted variables and perform other tests in regression directions, which are asymptotically valid in the presence of heteroskedasticity of unknown form.

We examine the asymptotic behaviour of these tests, and use Edgeworth approximations to study their approximate finite-sample performance.