# Probability weights with density estimation

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## Probability weights with density estimation

 I am a physician examining an NHANES dataset available at the NCHS website: http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/demo_d.xpthttp://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/hdl_d.xpthttp://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/tchol_d.xpt   Thank you to the R authors and the foreign package authors in particular. Importing from the SAS export fomat file was a snap. It consists of demographic data linked to laboratory measurements. Each subject has an associated sampling weight. I have gotten informative displays following the examples using kde2d() in V&R MASSe2 (more thanks), but these were unweighted analyses. The ratio of total cholesterol (TC) to HDL cholesterol is used clinically to estimate risk of future heart disease, and I am looking at how such ratios "divide" or intersect with the TC x HDL-C distribution. Rather than include all the real data, let me just post a simulation that shows a contourplot reasonably similar to what I am seeing. TC.ran <- exp(rnorm(400,1.5,.3)) HDL.ran <- exp(rnorm(400,.4,.3) ) f1<-kde2d(HDL.ran,TC.ran,n=25,lims=c(0,4,2,10)) contour(f1\$x,f1\$y,f1\$z,ylim=c(0,8),xlim=c(0,3),ylab="TC mmol/L",           xlab="HDL mmol/L") lines(f1\$x,5*f1\$x)   # iso-ratio lines lines(f1\$x,4*f1\$x) lines(f1\$x,3*f1\$x) Two questions: Is there a 2d density estimation function that has provision for probability weights (or inverse sampling probabilities)? I seem to remember a discussion on the list about whether such a procedure would be meaningful, but my searches cannot locate that thread or any worked examples that incorporate sampling weights. If there is such a function, would it be a simple matter to calculate the proportion of the total population that would be expected to have a ratio of y.ran/x.ran of less than a particular number, say 4.0? -- Respectfully; David Winsemius ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.