search for: alorithm

Dear all I'm trying to caculate the MLEs for parameters of Inverse Gaussian distribution (in a k-sample problem with common mean) by using EM-Algorithm. I found some package for EM-Algorithm that are useful for missing or incomplete data and are not helpful for solving my problem. (Exactly, the problem is: Let Xij, i=1,..,k , j=1,...,ni, be a random sample from IG(?,?i). So the

I have a data set with 6 variables and 251 cases. The people who supplied me with this data set believe that it falls naturally into three groups, and have given me a rule for determining group number from these 6 variables. If I do scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...)) stuff.dist <- dist(scaled.stuff) stuff.hc <- hclust(stuff.dist)

...ovided by the user to perform a Kerberos init against the Active Directory. A successful Kerberos init guarantees a correct password for this principal, and therefor the bind finally succeeds. Within this overlay operation, the password gets encrypted with the default OpenLDAP hash alorithm and stored as userPassword attribute. There is an option to update the sambaNTPassword also (using code borrowed from Howard Chu's smbk5pwd overlay). All following simple bind authentications will first try these cached credentials, making the OpenLDAP server independent from AD....

...ons could be done now only with left shift. I'm lack of time but won't be. Still it's not easy to create those matrixes from source code (especially 32-point). Would anyone send me those matrixes or manual how to create them? I'll do the multiplications and hand-optimization (I know alorithm to create application but this will be faster by hand). Or did anyone try this? Can anyone prove that this can't be faster? Even there's possibility to use MMX when working with matrixes. Is there any other such time critical piece of code that needs optimization? Send me a pointer and I...

Dear all, I would like to use the Levenberg-Marquardt algorithm for non-linear least-squares regression using function nls.lm. Can anybody help me to find a a way to compute confidence intervals on the fitted parameters as it is possible for nls (using confint.nls, which does not work for nls.lm)? Thank you for your help Michael