I am looking for a function that can fit a smooth function to a vector of estimated proportions, such that the smoothed value is within specified confidence bounds of each proportion. In other words, given a small number of trials and large confidence intervals, I would prefer the function to vary smoothly, but given a large number of trials and small confidence intervals, I would prefer the function to lie within the confidence intervals, even if it is not smooth.
I have attached a postscript file illustrating a data set I would like to smooth. As the figure shows, for large values of x, I have few data points, and so the ML estimate of the proportion varies widely, and the confidence intervals are very large. When I use the smooth.spline function with a large value of spar (the red line), the function is not as smooth as desired for large values of x. When I use a smaller value of spar (the green line), the function fails to stay within the confidence bounds of the proportions. Is there a smoothing function for which I can specify upper and lower limits for the y value for specific values of x? Thanks for any suggestions, Rose ______________________________________________ R-help@stat.math.ethz.ch 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.