huber.mu {asbio} | R Documentation |
The Huber M-estimator is a robust high efficiency estimator of location that has probably been under-utilized by biologists. It is based on maximizing the likelihood of a weighting function. This is accomplished using an iterative least squares process. The Newton Raphson algorithm is used here. The function usually converges fairly quickly (< 10 iterations). The function uses the Median Absolute Deviation function, mad
. Note that if MAD = 0, then NA
is returned.
huber.mu(x, c = 1.28, iter = 20, conv = 1e-07)
x |
A vector of quantitative data. |
c |
Stop criterion. The value |
iter |
Maximum number of iterations. |
conv |
Convergence criterion. |
Returns Huber's M-estimator of location.
Ken Aho
Huber, P. J. (2004) Robust Statistics. Wiley.
Wilcox, R. R. (2005) Introduction to Robust Estimation and Hypothesis Testing, Second Edition. Elsevier, Burlington, MA.
x <- rnorm(100) huber.mu(x)