vtreat cross frames

May 5, 2016
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vtreat cross frames

vtreat cross frames John Mount, Nina Zumel 2016-05-05 As a follow on to “On Nested Models” we work R examples demonstrating “cross validated training frames” (or “cross frames”) in vtreat. Consider the following data frame. The outcome only depends on the “good” variables, not on the (high degree of freedom) “bad” variables. Modeling such a … Continue reading...

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R 3.3.0 now available

May 5, 2016
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R 3.3.0 now available

R 3.3.0, a major annual update to the R Language, was released earlier this week and is now available from your local CRAN mirror for Windows, Mac (OSX 10.6 or later) and Linux systems. (Or as always, you can build it yourself from sources). This update — codenamed "Supposedly Educational" — makes a number of significant improvements to R,...

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Manipulate(d) Regression!

May 5, 2016
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Manipulate(d) Regression!

The R package ‘manipulate’ can be used to create interactive plots in RStudio. Though not as versatile as the ‘shiny’ package, ‘manipulate’ can be used to quickly add interactive elements to standard R plots. This can prove useful for demonstrating statistical concepts, especially to a non-statistician audience. The R code at the end of this

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NEWS of my BioC packages

May 5, 2016
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NEWS of my BioC packages

Today is my birthday and it happened to be the release day of Bioconductor 3.3. It’s again the time to reflect what I’ve done in the past year. ChIPseeker clusterProfiler DOSE ggtree GOSemSim ReactomePA ChIPseeker Although ChIPseeker was designed for ChIP-seq annotation, I am very glad to find that someone else use it to annotate other data including

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BioC 3.3: NEWS of my packages

May 5, 2016
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BioC 3.3: NEWS of my packages

Today is my birthday and it happened to be the release day of Bioconductor 3.3. It’s again the time to reflect what I’ve done in the past year. ChIPseeker clusterProfiler DOSE ggtree GOSemSim ReactomePA ChIPseeker Although ChIPseeker was designed for ChIP-seq annotation, I am very glad to find that someone else use it to annotate other data including

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BioC 3.3: NEWS of my packages

May 5, 2016
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BioC 3.3: NEWS of my packages

Today is my birthday and it happened to be the release day of Bioconductor 3.3. It’s again the time to reflect what I’ve done in the past year. ChIPseeker clusterProfiler DOSE ggtree GOSemSim ReactomePA ChIPseeker Although ChIPseeker was designed for ChIP-seq annotation, I am very glad to find that someone else use it to annotate other data including

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Links I liked

May 5, 2016
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Links I liked

The interwebs has been aflush with interesting data science material. Tweet     Big Five Personality Tests Have Never Been So Fun(ny) Tweet     Gelman on A Beautiful Sentiment Any time Gelman has something to say about graphics and methods, it’s useful. This seems like one of my first memories, though, of him...

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Need user feedback? Send it directly from R

May 5, 2016
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Need user feedback? Send it directly from R

Help Me, Help You As an R-dev, I’d like to know I’m meeting community need, as well as my own. But after an initial “aha!” moment, you don’t always know how to live up to the full potential of what you’ve started with a package. For example, RStudio collects extensive data through their products to better...

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Need user feedback? Send it directly from R

May 5, 2016
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via GIPHY Help Me, Help You As an R-dev, I’d like to know I’m meeting community need, as well as my own. But after an initial “aha!” moment, you don’t always know how to live up to the full potential of what you’ve started with a package. For example, RStudio collects extensive data through their products to better understand...

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Classify gender based on danish first names

May 5, 2016
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Classify gender based on danish first names

In Denmark we have official lists of what people are allowed to have as first names. That means there are lists of government approved boys names, girls names and unisex names. There is a total of 18.529 approved girls names, 15.052 boys names and 813 unisex names. This means that we can write an R-package... Read more »

Modeling in systems biology with R

May 4, 2016
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Modeling in systems biology with R

A couple of years ago, I was interested in a pharmacokinetic/pharmacodynamics (PK/PD) modeling and simulation project developed at the institute where I worked. It seemed that Matlab and its SimBiology toolbox was the tool everybody around me went with. While … Continue reading →

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11 new R jobs from around the world (2016-05-04)

May 4, 2016
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11 new R jobs from around the world (2016-05-04)

Here are the new R Jobs for 2016-05-04. To post your R job on the next post Just visit this link and post a new R job to the R community. You can either post a job for free, or pay a bit and have your job featured. Current R jobs Job seekers: please follow the links below to learn more and apply for your R job...

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How to install R packages on an off-line SQL Server 2016 instance

May 4, 2016
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by Andrie de Vries One of the most exciting features of the forthcoming release of SQL Server 2016 (generally available on June 1, and in preview now) is the ability to run R scripts directly in database using SQL Server R Services. This means your R code will run directly on the server, as opposed to first extracting the...

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R – GPU Programming for All with ‘gpuR’

May 4, 2016
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R – GPU Programming for All with ‘gpuR’

Introduction GPUs (Graphic Processing Units) have become much more popular in recent years for computationally intensive calculations.  Despite these gains, the use of this hardware has been very limited in the R programming language.  Although possible, the prospect of programming in either OpenCL or CUDA is difficult for many programmers unaccustomed to working with such

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acs version 2.0: an R package to download and analyze data from the US Census

May 4, 2016
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This is a re-post from the R packages mailing list We are pleased to announce the release of version 2.0 of the “acs” package, now available on CRAN <http://cran.r-project.org/web/packages/acs/index.html>. The package allows users to download, manipulate, analyze, and present demographic data from the U.S. Census, with special tools and methods to simplify the tasks of working with estimates and standard...

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RTCGA factory of R packages – Quick Guide

May 3, 2016
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Yesterday we have been delivered with the new version of R - R 3.3.0 (codename Supposedly Educational). This enabled Bioconductor (yes, not all packages are distributed on CRAN) to release it’s new version 3.3. This means that all packages held on Bioconductor, that were under rapid and vivid development, have been moved to...

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Because it’s Friday: The time-travelling jukebox

May 3, 2016
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Because it’s Friday: The time-travelling jukebox

If you're looking for some musical nostalgia this weekend, look no further than How Music Taste Evolved, from design firm Polygraph (and with a hat tip to Pogue). Choose any month from the past six decades, and then sit back and watch the top 5 songs on the Billboard chart of the day move up and down and listen...

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R 3.3.0 is released!

May 3, 2016
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R 3.3.0 is released!

R 3.3.0 (codename “Supposedly Educational”) was released today. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below. Upgrading to R 3.3.0 on Windows If you are using Windows you can easily upgrade to the latest version of R using the installr package. … Continue reading...

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Cross-Validation for Predictive Analytics Using R

May 3, 2016
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Cross-Validation for Predictive Analytics Using R

Cross-validation is a widely used model selection method. We show how to implement it in R using both raw code and the functions in the caret package. The post Cross-Validation for Predictive Analytics Using R appeared first on MilanoR.

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Numerical pitfalls in computing variance

May 3, 2016
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One of the most common tasks in statistical computing is computation of sample variance. This would seem to be straightforward; there are a number of algebraically equivalent ways of representing the sum of squares (S), such as or and...

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Using Docker as a Personal Productivity Tool – Running Command Line Apps Bundled in Docker Containers

May 3, 2016
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Using Docker as a Personal Productivity Tool – Running Command Line Apps Bundled in Docker Containers

With its focus on enterprise use, it’s probably with good reason that the Docker folk aren’t that interested in exploring the role that Docker may have to play as a technology that supports the execution of desktop applications, or at least, applications for desktop users. (The lack of significant love for Kitematic seems to be

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Build a Gradient Boosted Trees Model with Microsoft R Server

May 3, 2016
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Build a Gradient Boosted Trees Model with Microsoft R Server

by Yuzhou Song, Microsoft Data Scientist R is an open source, statistical programming language with millions of users in its community. However, a well-known weakness of R is that it is both single threaded and memory bound, which limits its ability to process big data. With Microsoft R Server (MRS), the enterprise grade distribution of R for advanced analytics,...

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Launch Bonuses for Shapefiles for R Programmers

May 3, 2016
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Launch Bonuses for Shapefiles for R Programmers

Yesterday I announced two webinars that I will be running to celebrate the launch of my new course, Shapefiles for R Programmers. Today I’m announcing two bonuses that I’m giving to people who buy the course by Thursday at 5pm PT: A 15% discount (save $15)! An invitation to a special Q&A webinar with me Click here to learn The post

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Introduction to R for Excel Users

May 3, 2016
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Introduction to R for Excel Users

When all you have is a hammer...Engineers and scientists, Excel is the hammer. #Rstats is a toolkit. Here's an intro.

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convert biological ID with KEGG API using clusterProfiler

May 3, 2016
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bitr_kegg clusterProfiler can convert biological IDs using OrgDb object via the bitr function. Now I implemented another function, bitr_kegg for converting IDs through KEGG API. library(clusterProfiler) data(gcSample) hg <- gcSample] head(hg) ## "4597" "7111" "5266" "2175" "755" "23046" eg2np <- bitr_kegg(hg, fromType='kegg', toType='ncbi-proteinid', organism='hsa') ## Warning in bitr_kegg(hg, fromType = "kegg", toType = "ncbi-proteinid", ## organism = "hsa"): 3.7% of input...

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convert biological ID with KEGG API using clusterProfiler

May 3, 2016
By

bitr_kegg clusterProfiler can convert biological IDs using OrgDb object via the bitr function. Now I implemented another function, bitr_kegg for converting IDs through KEGG API. library(clusterProfiler) data(gcSample) hg <- gcSample] head(hg) ## "4597" "7111" "5266" "2175" "755" "23046" eg2np <- bitr_kegg(hg, fromType='kegg', toType='ncbi-proteinid', organism='hsa') ## Warning in bitr_kegg(hg, fromType = "kegg", toType = "ncbi-proteinid", ## organism = "hsa"): 3.7% of input...

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googleformr updates on CRAN

May 3, 2016
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googleformr updates on CRAN

Main updates to googleformr have been to remove an internal dependency on magrittr chains in the function construction and to take http status checking outside of the main gformr function and into a check_form_works function. Both changes provide notable speed gains. One can still create a function with gformr as before: pacman::p_load(googleformr) form <- "your_google_form_url" my_fun <- gformr(form ...

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googleformr updates on CRAN

May 3, 2016
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Main updates to googleformr have been to remove an internal dependency on magrittr chains in the function construction and to take http status checking outside of the main gformr function and into a check_form_works function. Both changes provide notable speed gains. One can still create a function with gformr as before: form <- "your_google_form_url" my_fun <- googleformr::gformr(form ...

Read more »

convert biological ID with KEGG API using clusterProfiler

May 3, 2016
By

bitr_kegg clusterProfiler can convert biological IDs using OrgDb object via the bitr function. Now I implemented another function, bitr_kegg for converting IDs through KEGG API. library(clusterProfiler) data(gcSample) hg <- gcSample] head(hg) ## "4597" "7111" "5266" "2175" "755" "23046" eg2np <- bitr_kegg(hg, fromType='kegg', toType='ncbi-proteinid', organism='hsa') ## Warning in bitr_kegg(hg, fromType = "kegg", toType = "ncbi-proteinid", ## organism = "hsa"): 3.7% of input...

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