similar to: Very Fast Multivariate Kernel Density Estimation

Good evening! I have a multi-dimensional minimization problem whose gradient is pretty hard to code. I tried Nelder and Mead method implemented in function optim and it does not work well. I also tried the quasi Newton method in optim using difference as approximate derivative. It does not work well either. I just went through Numerical Recipes book. The book discusses another method without

without having to check the vector element by element? Thanks a lot! Jason ===== Jason G. Liao, Ph.D. Division of Biometrics University of Medicine and Dentistry of New Jersey 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-8611, fax (732) 235-9777 http://www.geocities.com/jg_liao

1. allows underscore as part of a variable name 2. Uses C or Java style comments mark. Jason ===== Jason G. Liao, Ph.D. Division of Biometrics University of Medicine and Dentistry of New Jersey 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-8611, fax (732) 235-9777 http://www.geocities.com/jg_liao __________________________________________________ HotJobs - Search

Hi Jason, I suppose you installed the Matrix library, and it is working on your computer? If yes, may be det.Matrix() was removed, or renamed in the Matrix library you have (I cannot check this for the latest version, because I am away of the office until August 1st), but I will do that next week. In the meantime, you can replace 'det.Matrix' by 'det.default', and it should run.

I have been using a laptop computer of Pentium III 1.13 Ghz. I heard that AMD's Athlon has excellent floating point capacity. So I bought a Athlon 2200+ laptop yesterday. I expected that new Athlon 2200+ will be twice as fast as the P III 1.13 GB. I ran a R simulation program and the new computer is only 30% faster, in fact slightly slower than a Celeron 1.50 GB laptop. I am very disappointed

Thanks to those who responded to my inquiry about generalized linear mixed models on R and S-plus. Before I summarize the software, I note that there are several ways of doing statistical inference for generalized linear mixed models: (1)Standard maximum likelihood estimation, computationally intensive due to intractable likelihood function (2) Penalized quasi likelihood or similar

I am excited to learn that Prof. Tierney is bringing to us compiled R. I would like to learn when it will be available. This information will be useful in scheduling some of my projects. Thanks. Jason Jason Liao, http://www.geocities.com/jg_liao Dept. of Biostatistics, http://www2.umdnj.edu/bmtrxweb University of Medicine and Dentistry of New Jersey 683 Hoes Lane West, Piscataway‚ NJ 08854

Hello, everyone! I guess no one is still using R on Sun Sparc these days. But our department has a (pretty new) two-CPU Sun server. We recently compiled R as a 64 bit application and expected a performance boost. But it runs 25-30% slower than the 32 bit version of R. Anyone knows why this is so? Thanks! Jason ===== Jason Liao, http://www.geocities.com/jg_liao Dept. of Biostatistics,

My coauthor made a new R package GeneLogit (100% R code) which installs ok on R 2.3 on Windows. But when I type library(GeneLogit) it gave the error message Error in library(GeneLogit) : 'GeneLogit' is not a valid package -- installed < 2.0.0? It runs on R 1.9.0 just fine. It seems that others have encountered same problem but no solution is found by googling How can I fix this

First, I love R and am grateful to be using this free and extremely high quality software. Recently I have been comparing two algorithms and naturally I programmed in R first. It is so slow that I can almost feel its pain. So I decided to do a comparison with Java. To draw 500,0000 truncated normal, Java program takes 2 second and R takes 72 seconds. Not a computer science major, I find it hard

Happy new month, everyone! I am planning to write a NIH grant proposal to study ways to speed Monte Carlo based maximum likelihood algorithm for hierarchical models with a focus on generalized linear mixed models (GLM with random effects). I thought it would be nice and also increase the chance of funding if I could produce an R package in the process. I understand that Prof. Pinheiro ang Bates

I did several simulation sessions and the result turned out to be a surprise. After some investigation, I found that different R sessions of the program used the same seed. Simply, in R210, if I start R and type rnorm(1), I always get the same random number. This is contradictary to what is in the R document Initially, there is no seed; a new one is created from the current time when one

First, happy holidays, everyone! Thanks to the R team for bringing out 1.4 before the new year. I have 10000 integer triplets stored in A[1:10000, 1:3]. I would like to find the unique triplets among the 10000 ones with possible duplications. What is the easiest way for this. I know the function unique(), which apply to a vector, not the 10000*3 array in my problem. Thanks in advance. Jason

I did some serach around. It seems that ROC curve computation is not supported on R. Anyone has some leads? Thanks. Jason ===== Jason G. Liao, Ph.D. Division of Biometrics UMDNJ School of Public Health 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-9748, fax (732) 235-9777 http://www.geocities.com/jg_liao __________________________________________________ Great

Good morning! I recently implemented a KD tree in JAVA for faster kernel density estimation (part of the code follows). It went well. To hook it with R, however, has proved more difficult. My question is: is it possible to implement the algorithm in R? My impression seems to indicate no as the code requires a complete class-object framework that R does not support. But is there an R package or

Dear R-list, I know is going to be weird, but I need to do something about and I know the R-list is big group of good people. I?m moving to Philadelphia in August 2009 (my fianc? is there) and I need to find a job. I know to do so many things, but my skill is in science and research. I would like to know if you know a possible position near Philadelphia, New Jersey or New York. I was working in

Can anybody, please, explain me how many parameter are estimated using randomLCA? For examples, model "dentistry.lca2random" estimate 1 scale (or variance, b_j) parameter and 2 position parameters (a_cj)? Doesn't it? Do I need at least 4 diagnostic tests for such a model? What happens if I specify options blocksize and byclass? How many diagnostic tests (or rater) I need?

The most likely explanation is you have a new version of dplyr/tibble and an old version of rlang. Try re-installing rlang. Hadley On Mon, Aug 14, 2017 at 9:26 AM, Szumiloski, John <John.Szumiloski at bms.com> wrote: > UseRs, > > When doing some data manipulations using the tidyverse, I am repeatedly getting the same error message in now three separate situations. I can write up

UseRs, When doing some data manipulations using the tidyverse, I am repeatedly getting the same error message in now three separate situations. I can write up a reproducible example, but want to lay out the high-level issues in case someone recognizes exactly what is happening here. The error is: Error in mut_env_parent(overscope$.top_env, lexical_env) : object 'rlang_mut_env_parent'

This sounds an awful lot like a bug. Read the Posting Guide to know what to do about bugs. And delaying making the reprex is _always_ a bad idea. -- Sent from my phone. Please excuse my brevity. On August 14, 2017 7:26:32 AM PDT, "Szumiloski, John" <John.Szumiloski at bms.com> wrote: >UseRs, > >When doing some data manipulations using the tidyverse, I am repeatedly