molic: An R package for multivariate outlier detection in contingency tables
نویسندگان
چکیده
منابع مشابه
rTableICC: An R Package for Random Generation of 2×2×K and R×C Contingency Tables
In this paper, we describe the R package rTableICC that provides an interface for random generation of 2×2×K and R×C contingency tables constructed over either intraclass-correlated or uncorrelated individuals. Intraclass correlations arise in studies where sampling units include more than one individual and these individuals are correlated. The package implements random generation of contingen...
متن کاملMultiple Factor Analysis for Contingency Tables in the FactoMineR Package
Abstract We present multiple factor analysis for contingency tables (MFACT) and its implementation in the FactoMineR package. This method, through an option of the MFA function, allows us to deal with multiple contingency or frequency tables, in addition to the categorical and quantitative multiple tables already considered in previous versions of the package. Thanks to this revised function, e...
متن کاملMultivariate Spatial Outlier Detection
A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. Previous work in spatial outlier detection focuses on detecting spatial outliers with a single attribute. I...
متن کاملOutlier Detection in Multivariate Data
The objective of this research is detection of outliers in multivariate data employing various distance measure, particularly using robust regression diagnosis technique. Several classical outlier identification methods are based on the sample mean and covariance matrix in general. But they do not always yield better result, as they themselves are affected by the outliers. Sometimes one outlier...
متن کاملMultivariate functional outlier detection
Functional data are occurring more and more often in practice, and various statistical techniques have been developed to analyze them. In this paper we consider multivariate functional data, where for each curve and each time point a p-dimensional vector of measurements is observed. For functional data the study of outlier detection has started only recently, and was mostly limited to univariat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Open Source Software
سال: 2019
ISSN: 2475-9066
DOI: 10.21105/joss.01665