search for: pdist

Hi, I want to compute the pairwise correlation for about 10,000 genes. In Matlab there is a function called 'pdsit' that can do this very efficiently. I am wondering is there a similar function in R? Thanks, RT Ye.

Hello , My optmatch package is loaded on R and otherwise running fine. I get an error after lcds successfully completes a logistic regression and I then try to obtain a propensity score: pdist <- pscore.dist(lcds) Error: could not find function "pscore.dist" Does anyone know if pscore.dist is part of the optmatch package, or is it contained in another package that I need to load? I searched the help files, other online sources, could find no answer for this. Any advice...

Hello My optmatch package is loaded and otherwise running fine. I get an error after lcds successfully completes logistic regression and I'm trying to obtain a propensity score: > pdist <- pscore.dist(lcds) Error: could not find function "pscore.dist" I searched the help files, other online sources, could find no answer for this. Any advice would be greatly appreciated! Thank you Michael Adolph

Hi All, Did anyone else have a problem like this? I am sorry if its a small issue, I seem to not understand what to do to get rid of this error. > Sigma [1] 0.1939025 > MuRest [1] 8.512772 > TauZero [1] 0.1 > curve(qlnorm(x,-TauZero+MuRest, Sigma,lower.tail=F), xlim=c(4000,9000), ylim=c(0,.99),xlab="", ylab="") Warning message: In qlnorm(p, meanlog, sdlog,

Hello all, I am fishing for some suggestions on efficient ways to make qdist and pdist type functions from an arbitrary distribution whose probability density function I've defined myself. For example, let's say I have a distribution whose pdf is: dRN <- function(x,d,v,s) # d, v, and s are parameters return(d/x^2/sv/sqrt(2*pi)*exp(-(d-v*x)^2/2/(sv^2*x^2))) this is...

>>> ted.harding at nessie.mcc.ac.uk 15/03/2007 13:26:52 >>> On 15-Mar-07 12:09:42, Eli Gurarie wrote: > Hello all, > > I am fishing for some suggestions on efficient ways to make qdist and > pdist type functions from an arbitrary distribution whose probability > density function I've defined myself. Ted Harding accurately said there is unliekly to be an efficient general answer. However, if you want a dreadfully inefficient but very general answer, could you use a numerical integra...

Hi all, Using the exponential distribution to exemplify: The dexp function is the PDF (1) and pexp is the CDF (2), that is obtained integrating the PDF. How can I get the qexp and the rexp? Considering that I have the PDF, how this two are mathematically related to the PDF? (1) ke^{-kx} (2) 1-e^{kx} Thanks in advance.