similar to: R consultant needed!

Os reenvío una oportunidad que ha llegado a R-jobs. Un saludo Patricia ---------- Forwarded message ---------- From: Joe O <jo5729@nododos.com> Date: 2010/11/16 Subject: [R-jobs] R consultant needed! To: "r-sig-jobs@r-project.org" <r-sig-jobs@r-project.org> Greetings! I have funding for some short term R consulting. I have written a spec for an NxN euclidean distance

Hello, I analyse some free-sorting data so I use hierarchical clustering. I want to compare my proximity matrix with the tree representation to evalute the fitting. (stress, cophenetic correlation (pearson's correlation)...) "The cophenetic similarity of two objects a and b is defined as the similarity level at wich objects a and b become members of the same cluster during the course of

Quantitative Health Risk Analysis Consultant Position open until filled Location: Boulder, CO We are a Colorado-based specialist risk and decision modeling consulting and research firm, with diverse experience and skills, including in the fields of human and veterinary health and epidemiology. We are currently seeking to fill a full-time position as a Quantitative Health Risk Analysis

Position: Quantitative Risk Analysis Consultant APPLICATIONS RECEIVED UNTIL JANUARY 9TH, 2017 Location: Fort Collins, CO (physical presence required) Position type: Full time We are a Colorado-based specialist risk and decision modeling consulting and research firm, with diverse experience and skills. We are seeking to fill a full-time position as a Quantitative Risk Analysis Consultant, to

Quantitative Risk and Decision Analysis Consultant Deadline for applications: May 31, 2016 Location: Boulder, CO We are currently looking for a motivated and talented senior consultant in Quantitative Risk and Decision Analysis who desires to use quantitative skills to make a difference in real-life problems. Responsibilities: - Framing and scoping of projects, and

Quantitative Risk and Decision Analysis Consultant Position open until filled Location: Boulder, CO We are currently looking for a motivated and talented consultant in Quantitative Risk and Decision Analysis who desires to use quantitative skills to make a difference in real-life problems. Responsibilities: - Framing and scoping of projects, and proposing of appropriate analytical

Hi, I would like to generate a correlation matrix with a particular structure. For example, a 3n x 3n matrix : A_(nxn) aI_(nxn) bI_(nxn) aI_(nxn) A_(nxn) cI_(nxn) aI_(nxn) cI_(nxn) A_(nxn) where - A_(nxn) is a *specified* symmetric, positive definite nxn matrix. - I_(nxn) is an identity matrix of order n - a, b, c are (any) real numbers Many attempts have been unsuccessful because a

************************************************************ Important: We would draw your attention to the notices at the bottom of this e-mail, particularly before opening and reviewing any file attachment(s). ************************************************************ Here is some code we have used. a<-array(c(1,.9,.7,.9,1,.3,.7,.3,1),dim=c(3,3)) a s<-eigen(a)$vectors

Anyone have any idea on this. I wanted to separate out my VirtualBox VDIs so that I could activate compression on the rest of the parent directory structure so I created a ZFS filesystem under my user directory. mv .VirtualBox .VirtualBox_orig zfs create /export/home/user/.VirtualBox zfs create /export/home/user/.VirtualBox/VDI zfs set compression=off /export/home/user/.VirtualBox/VDI zfs set

SELECTION FOR CONSULTANTS BY THE WORLD BANK REQUEST FOR EXPRESSIONS OF INTEREST All Submissions must be made via the World Bank Group's "eConsult2" system. Please go to: https://wbgeconsult2.worldbank.org/wbgec/index.html Click on "Business Opportunities", and find the following assignment: Assignment Title: 1067014 - Statistical Analyst with Extensive Experience in

Dear R-users, I am having trouble constructing nxn matrices involving calculations& conditions based on other tables. Below I describe a simple example of what I am trying to do: Given the Table A (n x m): Species1 Species2 X A1,1 A1,2 Y A2,1 A2,2 Z A3,1 A3,2 I want to create a matrix M (n xn) X Y Z X - M1,2 M1,3 Y M2,1 - M2,3 Z M3,1 M3,2 -

Hi all, I wonder if this kind of questions are ok in this list... Quick question: What does it mean than the rank of the QR decomposition of a NxN matrix is N-1 ? m: NxN matrix qr(m)$rank equal to (N-1) Long version: I'm doing a manova on a matrix of 10 variables and 16 observations. > dim(tmp) [1] 16 10 > fit <- manova( tmp ~ treatment*mouse ) >results <-

We are in the process of analyzing data from a discrete-choice conjoint survey and are looking for a consultant who can help us assess willingness to pay (WTP). We are currently able to assess overall WTP using the coefficients from our conjoint analysis but would like assistance in determining if significant differences in WTP exist across a number of subgroups via a segmented analysis or some

The Peabody Research Institute at Vanderbilt University is looking for a Consultant who can develop an R package for robust standard error calculations in meta-regression models. The consultant will be expected to translate an already developed R function into a more fully functional R package with additional analysis and output options. The ideal candidate will be an experienced R programmer who

Hello, I am working with a matrix of multilocus genotypes for ~180 individual snail samples, with substantial missing data. I am trying to calculate the pairwise genetic distance between individuals using the stats package 'dist' function, using euclidean distance. I took a subset of this dataset (3 samples x 3 loci) to test how euclidean distance is calculated: 3x3 subset used

*August 12, 2012* ** *Postdoctoral Researcher working on spatial models of marine wildlife, using R. * Integrated Statistics is looking for a post doctoral scientist to work with the Passive Acoustics Research Group and Large Whale Research Group, part of the Protected Species Branch at the Northeast Fisheries Science Center in Woods Hole, Massachusetts

Dear R-experts, Searching the help archives I found a recommendation to do multivariate outlier identification by mahalanobis distances based on a robustly estimated covariance matrix and compare the resulting distances to a chi^2-distribution with p (number of your variables) degrees of freedom. I understand that compared to euclidean distances this has the advantage of being scale-invariant.

Hello everyone! My data is composed of 277 individuals measured on 8 binary variables (1=yes, 2=no). I did two similar cluster analyses, one on SPSS 18.0 and one on R 2.9.2. The objective is to have the means for each variable per retained cluster. 1) the R analysis ran as followed: > call data > dist=dist(data,method="euclidean") >

> By the way, since the tcrossprod function in the Matrix package is so fast, the Euclidean distance can be computed very fast: Indeed. > euc_dist <- function(m) {mtm <- Matrix::tcrossprod(m); sq <- rowSums(m*m); sqrt(outer(sq,sq,"+") - 2*mtm)} There are two reasons why I didn't use this optimization in "wordspace": 1) It can be inaccurate for small

We are looking for a capable biostatistician or epidemiologist with sufficient exposure and knowledge of R in order to translate a series of legacy code into R compatible syntax files and perform statistical analyses on an as needed basis. Responsibilities: -- Translation of legacy syntax from Stata .do files into reproducible R compatible syntax files. -- Perform other statistical analyses as