Hi all, I am using the function COV.WT to estimate the estimators (location and scale) of a bivariate cauchy distribution. My doubt is about the option WT (weight), cause at the R-help shows that the weight is uniform according to the number of observations. But, checking the theory, for example, the mean is given by mean_estimator=mean(u(s)x)/mean(u(s)), where x=my data (bivariate) u(s)=(df+p/df+s), df=degree freedom, p=number parameters, s=mahalanobis distance The u(s) function is considered as a weight, in which gives more weight for the observations with a small mahalanobis distance. My question is, should I use this function u(s) as my weigth option at the COV.WT function. Is that clear! Thanks in advance, Marc -- View this message in context: http://www.nabble.com/ML-estimators-of-bivariate-cauchy-tp22124857p22124857.html Sent from the R help mailing list archive at Nabble.com.
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
