cov.wcomed: Weighted Co-Median Robust Covariance Matrix

Description Usage Arguments Value References Examples

View source: R/covariance.R

Description

See cov.comed for details on how the co-median matrix is calculated. The difference in this function is that the final covariance matrix is not based on dropping identified outliers, but rather, smoothly downweighting them.

Usage

1
cov.wcomed(x, hd = F, method = c("med", "hd", "aad"), iter = 2, k = 1.5)

Arguments

x

a data frame or matrix containing numeric variables

method

one of "med", "hd", or "aad". "med" uses the typical median and MAD. "hd" uses the Harrell-Davis estimate of the median in place of the median, and "aad" uses the average absolute deviation in lieu of the median absolute deviation. if option "aad" is used the appropriate consistency constant, sqrt(pi/2), is used instead of 1.4826. the only time "aad" is preferable is when there are columns in the data with a median absolute deviation of zero.

iter

number of refinement iterations

Value

a covRobust object containing the following elements:

References

Falk, M. (1997) On MAD and comedians. Annals of the Institute of Statistical Mathematics 49, 615-644.

Falk, M. (1998). A Note on the Comedian for Elliptical Distributions. Journal of Multivariate Analysis, 67(2), 306-317. doi:10.1006/jmva.1998.1775

Harrell, F. E. & Davis, C. E. (1982). A new distribution-free quantile estimator. Biometrika, 69, 635–640

Sajesh, T. A., & Srinivasan, M. R. (2012). Outlier detection for high dimensional data using the Comedian approach. Journal of Statistical Computation and Simulation, 82(5), 745-757. doi:10.1080/00949655.2011.552504

Examples

1

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.