R: Truncated Maximum Likelihood Estimates of Location and Scale
TML1.noncensored
R Documentation
Truncated Maximum Likelihood Estimates of Location and Scale
Description
This functions computes the truncated maximum likelihood estimates of location and scale
described in Marazzi and Yohai (2004).
It assumes that the error distribution is approximately Gaussian or log-Weibull.
The cut-off values for outlier rejection are fixed or adaptive.
This function is a simplified version of TML.noncensored for the case without covariates.
"logWeibull case" : list(tau=...,v=...) initial input estimates of location (tau) and scale (v).
control
Control parameters. For the default values, see the function TML1.noncensored.control.
...
If initial="S", parameters for the computation of the initial S estimates. See the function TML1.noncensored.control.S
for the default values.
Value
A list with the following components:
th0
Initial location estimate (S or input).
v0
Initial scale estimate (S or input).
nit0
Reached number of iteration if initial="S"
th1
Final location estimate.
v1
Final scale estimate.
nit1
Reached iteration number in IRLS algorithm for final estimate (only for the log_Weibull case).
tu, tl
Final cut-off values.
alpha
Estimated proportion of retained observations.
tn
Number of retained observations.
beta
Consistency constant for scale.
wi
Vector of weights (0 for rejected observations, 1 for retained observations).
CV0
Covariance matrix of the initial estimates (th0,v0).
CV1
Covariance matrix of the final estimates (th1,v1).
References
Marazzi A., Yohai V. (2004). Adaptively truncated maximum likelihood regression with asymmetric errors.
Journal of Statistical Planning and Inference, 122, 271-291.