[R] density estimation from interval-censored data

[David Firth]

I am aware of the nice R package "logspline", which does smooth 
density estimation from interval-censored data (that is, values that 
are known to lie in a specified interval rather than known exactly). 
Function logspline.fit uses a maximum penalized likelihood method, 
with the penalty related to the number of knots used in a cubic 
regression-spline fit.

I need to be able to do some things that don't seem straightforward 
with the logspline package:
   (a) penalize the likelihood also for roughness, e.g. using the 
integrated squared second derivative
   (b) obtain approximate confidence limits for the density at specified points

My question: is there another R package that can help me with these 
things?  If so it would be good to know before I embark on 
programming them myself.

Thanks -- David
-- 


David Firth                        Phone +44 1865 278544
Nuffield College                   Fax   +44 1865 278621
Oxford OX1 1NF                     Secretary +44 1865 278553
United Kingdom                     Email david.firth at nuffield.ox.ac.uk

http://www.stats.ox.ac.uk/~firth/
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