𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Detection of outliers and robust estimation using fuzzy clustering

✍ Scribed by Bernard Van Cutsem; Isak Gath

Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
962 KB
Volume
15
Category
Article
ISSN
0167-9473

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Outlier Detection in Regression Models w
Outlier Detection in Regression Models with ARIMA Errors using Robust Estimates
✍ A. M. Bianco; M. GarcΓ­a Ben; E. J. MartΓ­nez; V. J. Yohai πŸ“‚ Article πŸ“… 2001 πŸ› John Wiley and Sons 🌐 English βš– 130 KB

## Abstract A diagnostic procedure for detecting additive and innovation outliers as well as level shifts in a regression model with ARIMA errors is introduced. The procedure is based on a robust estimate of the model parameters and on innovation residuals computed by means of robust filtering. A M

Robust Hierarchical Bayes Estimation of
Robust Hierarchical Bayes Estimation of Small Area Characteristics in the Presence of Covariates and Outliers
✍ G.S. Datta; P. Lahiri πŸ“‚ Article πŸ“… 1995 πŸ› Elsevier Science 🌐 English βš– 642 KB

A robust hierarchical Bayes method is developed to smooth small area means when a number of covariates are available. The method is particularly suited when one or more outliers are present in the data. It is well known that the regular Bayes estimators of small area means, under normal prior distri

Estimation of time-to-failure distributi
Estimation of time-to-failure distribution derived from a degradation model using fuzzy clustering
✍ Shuo-Jye Wu; Tzong-Ru Tsai πŸ“‚ Article πŸ“… 2000 πŸ› John Wiley and Sons 🌐 English βš– 100 KB πŸ‘ 1 views

Some life tests are terminated with few or no failures. In such cases, a recent approach is to obtain degradation measurements of product performance that may contain some useful information about product reliability. Generally degradation paths of products are modeled by a nonlinear regression mode

Connectivity of the mutual k-nearest-nei
Connectivity of the mutual k-nearest-neighbor graph in clustering and outlier detection
✍ M.R. Brito; E.L. ChΓ‘vez; A.J. Quiroz; J.E. Yukich πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 610 KB

For multivariate data sets, we study the relationship between the connectivity of a mutual k-nearest-neighbor graph, and the presence of clustering structure and outliers in the data. A test for detection of clustering structure and outliers is proposed and its performance is evaluated in simulated