modi: modi: Multivariate outlier detection for incomplete survey...

In modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data

modi: Multivariate outlier detection for incomplete survey data.

Description

The package modi is a collection of functions for multivariate outlier detection and imputation. The aim is to provide a set of functions which cope with missing values and take sampling weights into account. The original functions were developed in the EUREDIT project. This work was partially supported by the EU FP5 ICT programme, the Swiss Federal Office of Education and Science and the Swiss Federal Statistical Office. Subsequent development was in the AMELI project of the EU FP7 SSH Programme and also supported by the University of Applied Sciences and Arts Northwestern Switzerland (FHNW).

modi functions

BACON-EEM algorithm in BEM(), Epidemic algorithm in EAdet() and EAimp(), Transformed Rank Correlations in TRC(), Gaussian imputation with MCD in GIMCD().

References

Béguin, C., and Hulliger, B. (2004). Multivariate outlier detection in incomplete survey data: The epidemic algorithm and transformed rank correlations. Journal of the Royal Statistical Society, A167 (Part 2.), pp. 275-294.

Béguin, C., and Hulliger, B. (2008). The BACON-EEM Algorithm for Multivariate Outlier Detection in Incomplete Survey Data, Survey Methodology, Vol. 34, No. 1, pp. 91-103.

modi documentation built on March 31, 2023, 8:35 p.m.