search for: bivar

I have 10000 bivarate samples (x1, x2), and I want to estimate the marginal density of x2. I searched the R manual but couldn't find a function that can do this job. It seems "density" only works for single-variate samples. Can anybody help me with it? Thanks a lot! Best, J. Deng

Hi All I am trying to translate a proc mixed into a lme() syntax. It seems that I was able to do it for part of the model, but a few things are still different. It is a 2-level bivariate model (some call it a pseudo-3-level model). PROC MIXED DATA=psdata.bivar COVTEST METHOD = ml; CLASS cluster_ID individual_id variable_id ; MODEL y = Dp Dq / SOLUTION NOINT; RANDOM Dp Dq / SUBJECT = cluster_ID TYPE=UN G GCORR; REPEATED variable_id / SUBJECT = individual_ID(cluster_ID) TYPE=UN...

...d in this software. I looked in R for meta-analysis functions but the packeges available dont work with diagnostic tests. Im trying for a while to adapt in R a function develped in SAS and published in "J.B. Reitsma et al. / Journal of Clinical Epidemiology 58 (2005) 982?990", wich is a bivariate approach to meta-analysis of diagnotic tests. Since I do not have any experience with SAS, Im having a hard time trying to do so. There is an appendix at the original text with some step by step (in SAS syntax) on how to do it but Im stuck on a more advanced stuff which I cant find a solution...

...for a statistics tutorial I want to develop a nice 3d-graphic of the well known target comparison/analogy of accuracy and precision (see i.e. http://en.wikipedia.org/wiki/Accuracy_and_precision for a simple hand made 2d graphic). The code for a really beautiful graphic is already provided as demo(bivar) in the rgl package (for a picture see i.e http://rgl.neoscientists.org/gallery.shtml right upper corner). Now I'd like to add the standard deviation to the 3d plot. Unfortunately I couldn't figure out how to do that. What I did so far is: Assuming you have executed the code of the demo...