May 2015

Predicting events, when they haven’t happened yet

May 5, 2015 | Markus Gesmann

Suppose you have to predict the probabilities of events which haven't happened yet. How do you do this?Here is an example from the 1950s when Longley-Cook, an actuary at an insurance company, was asked to price the risk for a mid-air collision of two p...

[Read more...]

Data Mining the California Solar Statistics with R: Part II

May 4, 2015 | John

Data Mining the California Solar Statistics with R: Part II In today's post I'll be working some more with the working data set from California Solar Statistics. Last time I imported the data, cleaned it up a bit, grouped it by county and year, and made some plots to look ...

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Clusters May Be Categorical but Cluster Membership Is Not All-or-None

May 4, 2015 | Joel Cadwell

Very early in the study of statistics and R, we learn that random variables can be either categorical or continuous. Regrettably, we are forced to relearn this distinction over and over again as we debug error messages produced by our code (e.g., ... [Read more...]

RcppAnnoy 0.0.6

May 4, 2015 | Thinking inside the box

A few days ago, Erik released a new version of his Annoy library -- a small, fast, and lightweight C++ template header library for approximate nearest neighbours -- which now no longer requires Boost. While I don't mind Boost (actually, quite the op... [Read more...]

take those hats off [from R]!

May 4, 2015 | xi'an

This is presumably obvious to most if not all R programmers, but I became aware today of a hugely (?) delaying tactic in my R codes. I was working with Jean-Michel and Natesh [who are visiting at the moment] and when coding an MCMC run I was telling them that I ...

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Working with “large” datasets, with dplyr and data.table

May 4, 2015 | arthur charpentier

A few months ago, I was doing some training on data science for actuaries, and I started to get interesting puzzeling questions. For instance, Fleur was working on telematic data, and she’s been challenging my (rudimentary) knowledge of R. As claimed by Donald Knuth, “we should forget about small ... [Read more...]

Call R and Python from base SAS

May 4, 2015 | David Smith

Since 2009, it has been possible to call R from SAS programs. However, this integration requires IML, an add-on matrix-object language for SAS which isn't available with all SAS installations and is separate from the standard SAS PROC execution model. Now, engineers at SAS have shared a method of calling R, ... [Read more...]

using GOSemSim to rank proteins obtained by co-IP

May 4, 2015 | R on Guangchuang Yu

Co-IP is usually used to identified interactions among specific proteins. It is widely used in detecting protein complex. Unfortunately, an identified protein may not be an interactor, and sometimes can be a background contaminant. Ranking proteins can help us to focus a study on a few high quality candidates for ...

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Geomorph beta in development (2.1.5)

May 3, 2015 | Emma Sherratt

Dear geomorph users,We've been busy adding some new functions to the forthcoming v.2.1.5, currently in beta stage and available on gitHub (installed using: devtools::install_github("EmSherratt/geomorph",ref = "Develop")). Users be aware that ... [Read more...]

dplyr Tutorial: verbs + split-apply-combine

May 3, 2015 | dgrapov

At a recent Saint Louis R users meeting I had the pleasure of giving a basic introduction to the awesome dplyr R package. For me, data analysis ubiquitously involves splitting the data based on grouping variable and then applying some function to the subsets or what is termed split-apply-combine. Having ... [Read more...]

dplyr Tutorial: verbs + split-apply

May 3, 2015 | dgrapov

Cohort Analysis with Heatmap

May 3, 2015 | Analyze Core » R language

Previously I shared the data visualization approach for descriptive analysis of progress of cohorts with the “layer-cake” chart (part I and part II). In this post, I want to share another interesting visualization that not only can be used for descriptive analysis as well but would be more helpful for ...

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Introducing Radiant: A shiny interface for R

May 3, 2015 | R(adiant) news

Radiant is a platform-independent browser-based interface for business analytics in R, based on the Shiny package. Key features Explore: Quickly and easily summarize, visualize, and analyze your data Cross-platform: It runs in a browser on Windows, Mac, and Linux Reproducible: Recreate results at any time and share work with others ... [Read more...]

Survival Analysis With Generalized Additive Models : Part IV (the survival function)

May 2, 2015 | Christos Argyropoulos

The ability of PGAMs to estimate the log-baseline hazard rate, endows them with the capability to be used as smooth alternatives to the Kaplan Meier curve. If we assume for the shake of simplicity that there are no proportional co-variates in the PGAM regression, then the quantity modeled corresponds to ...

$S(t)$

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Update to Introduction to programming econometrics with R

May 2, 2015 | Bruno Rodrigues

This semester I taught a course on applied econometrics with the R programming language. For this, I created a document that I gave to my students and shared online. This is the kind of document I would have liked to read when I first started using R. I already had ... [Read more...]

Survival Analysis With Generalized Additive Models : Part III (the baseline hazard)

May 2, 2015 | Christos Argyropoulos

In the third part of the series on survival analysis with GAMs we will review the use of the baseline hazard estimates provided by this regression model. In contrast to the Cox mode, the log-baseline hazard is estimated along with other quantities (e.g. the log hazard ratios) by the ...

$log(h(t_{i,j})) = \beta_{0}+\lambda(t_{t,j})+\boldsymbol{x\beta} = \lambda_{I}(t_{i,j})+\boldsymbol{x\beta}$

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Survival Analysis With Generalized Models: Part II (time discretization, hazard rate integration and calculation of hazard ratios)

May 2, 2015 | Christos Argyropoulos

In the second part of the series we will consider the time discretization that makes the Poisson GAM approach to survival analysis possible. Consider a set of s individual observations at times , with censoring indicators assuming the value of 0 if the corresponding observation was censored and 1 otherwise. Under the assumption ...

$\mathcal{D}=\left\{ \delta_{i}\right\} _{i=1}^{M}$

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Rcpp 0.11.6

May 2, 2015 | Thinking inside the box

The new release 0.11.5 of Rcpp arrived on the CRAN network for GNU R yesterday; the corresponding Debian package has also been uploaded. Rcpp has become the most popular way of enhancing GNU R with C++ code. As of today, 373 packages on CRAN depend o... [Read more...]

Automated Animated Choropleth

May 2, 2015 | AdventuresInData

Here's an animated choropleth (graph using colored map shapes) of HUC8 watersheds in the Delaware River Basin showing water yield over a span of 20 days. The script is fully automated, pulling USGS gage data from NWIS, computing the water yield t... [Read more...]

RcppArmadillo 0.5.100.1.0

May 2, 2015 | Thinking inside the box

A new minor release 5.100.1 of Armadillo was released by Conrad yesterday. Armadillo is a powerful and expressive C++ template library for linear algebra aiming towards a good balance between speed and ease of use with a syntax deliberately close to a Matlab. Our corresponding RcppArmadillo release 0.5.100.1.0 also reached CRAN and ... [Read more...]

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R-bloggers

R news and tutorials contributed by hundreds of R bloggers

May 2015

Predicting events, when they haven’t happened yet

Data Mining the California Solar Statistics with R: Part II

Clusters May Be Categorical but Cluster Membership Is Not All-or-None

RcppAnnoy 0.0.6

take those hats off [from R]!

Working with “large” datasets, with dplyr and data.table

Call R and Python from base SAS

using GOSemSim to rank proteins obtained by co-IP

Geomorph beta in development (2.1.5)

dplyr Tutorial: verbs + split-apply-combine

dplyr Tutorial: verbs + split-apply

Cohort Analysis with Heatmap

Introducing Radiant: A shiny interface for R

Survival Analysis With Generalized Additive Models : Part IV (the survival function)

Update to Introduction to programming econometrics with R

Survival Analysis With Generalized Additive Models : Part III (the baseline hazard)

Survival Analysis With Generalized Models: Part II (time discretization, hazard rate integration and calculation of hazard ratios)

Rcpp 0.11.6

Automated Animated Choropleth

RcppArmadillo 0.5.100.1.0

May 2015

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