Robust univariate location and scale M-estimators
This function computes M-estimators for location and scale.
locScaleM(x, psi = "mopt", eff = 0.95, maxit = 50, tol = 1e-04, na.rm = FALSE)
x |
a vector of univariate observations |
psi |
a string indicating which score function to use. Valid options are "bisquare", "huber", "opt" and "mopt". |
eff |
desired asymptotic efficiency. Valid options are 0.85, 0.9 and 0.95 (default) when
|
maxit |
maximum number of iterations allowed. |
tol |
tolerance to decide convergence of the iterative algorithm. |
na.rm |
a logical value indicating whether |
This function computes M-estimators for location and scale.
A list with the following components:
mu |
The location estimate |
std.mu |
Estimated standard deviation of the location estimator |
disper |
M-scale/dispersion estimate |
Ricardo Maronna, rmaronna@retina.ar
set.seed(123) r <- rnorm(150, sd=1.5) locScaleM(r) # 10% of outliers, sd of good points is 1.5 set.seed(123) r2 <- c(rnorm(135, sd=1.5), rnorm(15, mean=-10, sd=.5)) locScaleM(r2)
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