similar to: Non-parametric predictive modelling consultant required

Hi All, Just thought you might be interested in a recently released R package, spm: Spatial Predictive Modelling. It aims to introduce some novel, accurate, hybrid geostatistical and machine learning methods for spatial predictive modelling. Of 22 functions available in spm, two functions are for accuracy assessment. Perhaps they are not only useful tools for spatial predictive modelling

Dear R users, A new version (1.1.0) of the ?spm? package for spatial predictive modelling is now available on CRAN. The introductory vignette is available here: https://cran.rstudio.com/web/packages/spm/vignettes/spm.html There are several new enhancements to the package including a fast version of random forest in using ranger (rg) library(ranger) and the ability to convert relevant

Version 1.2.0 of pmml has been released and is available from CRAN. The pmml package (http://rattle.togaware.com/pmml.html) is part of the Rattle data mining suite http://rattle.togaware.com. It generates representations of analytic models built in R using the open standard predictive modelling markup language (http://www.dmg.org/). PMML represents analytic models in an application independent

Version 1.2.0 of pmml has been released and is available from CRAN. The pmml package (http://rattle.togaware.com/pmml.html) is part of the Rattle data mining suite http://rattle.togaware.com. It generates representations of analytic models built in R using the open standard predictive modelling markup language (http://www.dmg.org/). PMML represents analytic models in an application independent

I'm a newcomer to llvm, but what you've done so far is very impressive. Llvm is a godsend to anybody who is attempting to implement their own their own language. :-) My company is considering using llvm as the backend for a small matlab-like language for scientific computation; our other option is MSIL. After reading through the documentation, I noticed that llvm seems to have one major

Would anybody be able to advise on which package would offer the best approach for producing a model able to predict the probability of species occupation based upon a range of variables, some of them catagorical (eg. ten soil types where the numbers assigned are not related to any qualitative/quantitative continuum or vegetation type) and others continuous such as field size or vegetation height.

Dear list, I?m wondering if there is something analogous to the TukeyHSD function that could be used for parametric terms in a GAM. I?m using the mgcv package to fit models that have some continuous predictors (modeled as smooth terms) and a single categorical predictor. I would like to do post hoc test on the categorical predictor in the models where it is significant. Any suggestions?

hi all i have a another stats question. i would like to solve the following question: y(i)=a+b*x(i)+e(i) i.e. estimate a and b (they should be fixed) but i dont want to specify the standard density to the straight line. this can be done using kernel regression. the fitted line is however fitted locally. does anyone have a reference that will help me with my problem. i am still new to

R-Listers. The following is a rant originally sent privately to Frank Harrell in response to remarks he made on this list. The ideas are not new or original, but he suggested I share it with the list, as he felt that it might be of wider interest, nonetheless. I have real doubts about this, and I apologize in advance to those who agree that I should have kept my remarks private. In view of this,

I am seeing extremely slow performance with glusterfs. OS: CentOS 5 glusterfs version: glusterfs-1.3.9-1 Server configuration: ############################################## ### GlusterFS Server Volume Specification ## ############################################## #### CONFIG FILE RULES: ### "#" is comment character. ### - Config file is case sensitive ### - Options within a

I am new to R. I'm using the function GAM and wanted to get standard errors and p-values for the parametric terms (I fitted a semi-parametric models). Using the function anova() on the object from GAM, I only get p-values for the nonparametric terms. Does anyone know if and how to get standard errors for the parametric terms? Thanks. Jean G. Orelien

Hi, I am trying to estimate the sample size needed for the comparison of two groups on a certain measurement, given some previous data at hand. I find that the data collected does not follow a normal distribution, so I would like to use a non-parametric option for sample size calculation. I found the pwr package but I don't think it has this option and on the internet found that

Hi UseRs, Please find the Job Description posted below. Our organization is looking for people with strong quantitative skills who is also strong in programming with R. Do get in touch with Prabhanshu (prabhanshu.pandey at 247customer.com) if you consider your experience and skills a good fit for the roles below. Location: *Bangalore, India* Let me know if you need any further clarification.

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

Hi all, I wanted to let you know about our training seminar on predictive analytics - coming May, Oct, and Nov in NYC, Stockholm, DC and other cities. This is intensive training for marketers, managers and business professionals to make actionable sense of customer data by predicting buying behavior, churn, etc. Past attendees provided rave reviews. Here's more info:

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Can anyone suggest a good non-parametric test, and an R implementation of the test, that allows for two or more factors? Wilcoxon signed rank allows for only one. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC and University of Maryland School of Medicine Claude Pepper OAIC University of Maryland School of Medicine Division of

Hi everyone, Predictive Analytics World's program for Feb 18-19 in San Francisco (www.predictiveanalyticsworld.com) has grown a bit since my post several weeks ago, and is looking better than ever. The conference covers today's commercial deployment of predictive analytics, across industries and across software vendors. In a nutshell, PAW is a warehouse of case studies. In breaking

Hi * i'm trying to do my statistical analysis with R (on a debianGNULinux) i've installed R and now i'll try to import my data from .xls Where to search for non parametric test in R ? I'm studing neurons velocity and i've to check if after the perfusion with a factor x the velocity changes but as my variable is not normally ditributed i've to try with non parametric