Description Usage Arguments Value References Examples
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.
1 | cov.wcomed(x, hd = F, method = c("med", "hd", "aad"), iter = 2, k = 1.5)
|
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 |
a covRobust object containing the following elements:
center: multivariate mean of cleaned data set after discarding outliers identified by the mahalanobis distances of the co-median matrix.
cov: covariance matrix of cleaned data set after discarding outliers identified by the mahalanobis distances of the co-median matrix.
medians: estimated columnwise medians
com: estimated co-median matrix
delta: the initial raw comedian correlation matrix
dist: the mahalanobis distances based on the cleaned covariance matrix
distL1: the mahalanobis distances based on the co-median matrix
outliers: the indices of the outliers identified by the co-median matrix based mahalanobis distances; these are the points removed to obtain the cleaned covariance matrix.
weights: the weights for downweighting outliers.
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
1 | cov.wcomed(x)
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