I have a problem either understanding what loess is doing or that loess has a problem itself.
As the x-axis variables become more concentrated on a particular point,the estimated loess tends to zero????. the examples below show what i am talking about, why is that? my intution tells me that it should tend to the mean of the variable which is been smoothed. Here's a worked up example x <- c(seq(0,100), rep(100,1000)) y <- rnorm(length(x), mean=10, sd=2) scatter.smooth(x,y) Although it does give warnings, I don't understand why it is giving the estimate as zero. another example would be x <- seq(0,100) y <- rnorm(length(x), mean=50, sd=2) scatter.smooth(x,y, span=1/length(x)) shoudn't this give just the points at which the smoothing algorithm is applied? thank you ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
