Animations Understood

May 11, 2013
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Animations Understood

When I first saw a graphic made from Yihui’s animation package (Xie, 2013) I was amazed at the magic and thought “I could never do that”. Passage of time… One night I found myself bored and as usual avoiding work. … Continue reading →

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Reproducibility and randomness

May 11, 2013
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Reproducibility and randomness

With Stéphane Tufféry, we were working this week on a chapter of a book, entitled Statistical Learning in Actuarial Science. The chapter should be based on R functions, and we wanted to reproduce some outputs he previously obtained with SAS. The good thing is that even complex functions (logistic regression, regression trees, etc) produce the same kind of outputs....

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Veterinary Epidemiologic Research: Count and Rate Data – Poisson Regression and Risk Ratios

May 10, 2013
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Veterinary Epidemiologic Research: Count and Rate Data – Poisson Regression and Risk Ratios

As noted on paragraph 18.4.1 of the book Veterinary Epidemiologic Research, logistic regression is widely used for binary data, with the estimates reported as odds ratios (OR). If it’s appropriate for case-control studies, risk ratios (RR) are preferred for cohort studies as RR provides estimates of probabilities directly. Moreover, it is often forgotten the assumption

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Spatial Critter Swarming Simulation

May 10, 2013
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Spatial Critter Swarming Simulation

# I am interested in how small bits of individualized instructions can create collective action.# In this simulation I will give a single instruction to each individual in the swarm.# Choose another individual who is not too close, then accelerate towards that individual.# I also control momentum causing the previous movement and direction to...

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A guide to speeding up R code

May 10, 2013
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Noam Ross recently shared a very useful guide to speeding up your R code. Get a bigger computer (for example, renting an instance on the Amazon cloud for a few cents an hour) Use parallel programming techniques Using the R byte-compiler Profiling and benchmarking your code Using high-performance packages (like xts, for time series) And lastly, rewriting your code...

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Tutorials on git/github and GNU make

May 10, 2013
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Tutorials on git/github and GNU make

If you’re not using version control, you should be. Learn git. If you’re not on github, you should be. That’s real open source. To help some colleagues get started with git and github, I wrote a minimal tutorial. There are lots of git and github resources available, but I thought I’d give just the bare

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Using Interactive D3.js charts from within Tiki with rNVD3

May 10, 2013
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Using Interactive D3.js charts from within Tiki with rNVD3

I've recently managed to reproduce my first charts using the nice package rNVD3 from Ramnath Vaidyanathan: https://github.com/ramnathv/rNVD3 This rNVD3 package uses NVD3, which provides re-usable charts with d3.js, without taking away the power that...

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Using Interactive D3.js charts from within Tiki with rNVD3

May 10, 2013
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Using Interactive D3.js charts from within Tiki with rNVD3

I've recently managed to reproduce my first charts using the nice package rNVD3 from Ramnath Vaidyanathan: https://github.com/ramnathv/rNVD3 This rNVD3 package uses NVD3, which provides re-usable charts with d3.js, without taking away the power that...

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Bubble sort implemented in pure R

May 10, 2013
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Bubble sort implemented in pure R

Please note that this is programming I purely did for the learning experience. The pure R bubble sort implemented in this post is veeeeery slow for two reasons: Interpreted code with lots of iteration is very slow. Bubble sort is… See more ›

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Package intergraph goes 2.0

May 9, 2013
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Yesterday I submitted a new version (marked 2.0-0) of package ‘intergraph’ to CRAN. There are some major changes and bug fixes. Here is a summary: The package supports “igraph” objects created with ‘igraph’ version 0.6-0 and newer (vertex indexing starting from 1, not 0) only! Main functions for converting network data between object classes “igraph”

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Medicare Provider Charge Data – How Are Things in Spokane?

May 9, 2013
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Medicare Provider Charge Data – How Are Things in Spokane?

Disclosure: I am not a health care professional, but just some one interested in playing with data and ways to represent them. I am not going to interpret findings here, but will make a remark or two about how to interpret them from the few graphs...

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What’s Next

May 9, 2013
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The last two weeks have been full of changes for me. For those who’ve been asking about what’s next, I thought I’d write up a quick summary of all the news. (1) I successfully defended my thesis this past Monday. Completing a Ph.D. has been a massive undertaking for the past five years, and it’s

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How R Grows – not so fast

May 9, 2013
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How R Grows – not so fast

I have had some work on CRAN stats on the back-burner but the recent article How R Grows tempted me to push it up the list In the interim, I have a couple of comments on Joseph Rickert`s article. Although the body of the article refers to packages either created or updated in a time

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R is His Friend

May 9, 2013
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Marcus Beck has a nice (& relatively new) blog called R is My Friend. You can guess that his posts relate to the use of R.I particularly liked his piece on the use of the XML package in R to mine data from the internet; and his post on using the integrate...

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Trevor Hastie presents glmnet: lasso and elastic-net regularization in R

May 9, 2013
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Trevor Hastie presents glmnet: lasso and elastic-net regularization in R

by Joseph Rickert Even a casual glance at the R Community Calendar shows an impressive amount of R user group activity throughout the world: 45 events in April and 31 scheduled so far for May. New groups formed last month in Knoxville, Tennessee (The Knoxville R User Group: KRUG) and Sheffield in the UK (The Sheffield R Users). An...

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Omni test for statistical significance

May 9, 2013
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Omni test for statistical significance

In survey research, our datasets nearly always comprise variables with mixed measurement levels – in particular, nominal, ordinal and continuous, or in R-speak, unordered factors, ordered factors and numeric variables. Sometimes it is useful to be able to do blanket tests of one set of variables (possibly of mixed level) against another without having to

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Reading an R file from GitHub

Reading an R file from GitHub

Lets say that I want to read in this R file from GitHub into R. The first thing you have to do is locate the raw file. You can do so by clicking on the Raw button in GitHub. In this case it’s https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R One would think that using source() would work, but it doesn’t as shown below: source("https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R") ##...

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Version 0.9 of timeline on CRAN

May 9, 2013
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Version 0.9 of timeline on CRAN

The initial version of the timeline package has been released to CRAN. This package provides creates timeline plots using ggplot2 in a style similar to Preceden. I would considered this beta quality as there are more features I would like to add but has enough functionality to possibly be useful to others. install.packages('timeline',repos='http://cran.r-project.org') require(timeline) data(ww2) timeline(ww2, ww2.events, event.spots=2, event.label='', event.above=FALSE) Timeline...</p><p><a href=Read more »

A Shiny web app to find out how much medical procedures cost in your state.

May 8, 2013
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A Shiny web app to find out how much medical procedures cost in your state.

Today the front page of the Huffington Post featured the new data available from the CMS that shows the cost of many popular procedures broken down by hospital. We here at Simply Statistics think you should be able to explore … Continue reading →

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What’s new in Revolution R Enterprise 6.2 (video)

May 8, 2013
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If you missed last week's webinar, product manager Thomas Dinsmore shared details of the new features in Revolution R Enterprise 6.2 in the video below: You can also download slides of the presentation at the link below. Revolution Analytics webinars: What's New in Revolution R Enterprise 6.2

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Computed columns for dataframes

May 8, 2013
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Computed columns for dataframes

Everyone loves to aggregate data. Everyone loves to create new columns based on other columns. Everyone hates to do the same thing twice. In my continuing work on multilevel view of loss reserving, I reached a point where I realized that I needed a robust mechanism to aggregate computed columns. SQL server and (I’m assuming)

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Feature Selection 2 – Genetic Boogaloo

May 8, 2013
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Feature Selection 2 – Genetic Boogaloo

Previously, I talked about genetic algorithms (GA) for feature selection and illustrated the algorithm using a modified version of the GA R package and simulated data. The data were simulated with 200 non-informative predictors and 12 linear effects and three non-linear effects. Quadratic discriminant analysis (QDA) was used to model the data. The last set of...

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3D Mapping in R

May 8, 2013
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3D Mapping in R

This tutorial has been kindly contributed by Robin Edwa

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SAS, SPSS, Stata Users: Learn R from Home June 17

May 8, 2013
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SAS, SPSS, Stata Users: Learn R from Home June 17

Has learning R been driving you a bit crazy? If so, it may be that you’re “lost in translation.” On June 17 and 19, I’ll be teaching a webinar, R for SAS, SPSS and Stata Users. With each R concept, … Continue reading →

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Building a custom database of country time-series data using Quandl

May 8, 2013
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Building a custom database of country time-series data using Quandl

Encouraged by this post I had another look at quandl for collecting datasets from different agencies. Right now I need to get data for four countries on a couple of dozen indicators. This graphic is just a quick example with only two indicators of what I am aiming to be able to do. The process

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An accept-reject sampler using RcppArmadillo::sample()

May 8, 2013
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An accept-reject sampler using RcppArmadillo::sample()

The recently added RcppArmadillo::sample() functionality provides the same algorithm used in R’s sample() to Rcpp-level code. Because R’s own sample() is written in C with minimal work done in R, writing a wrapper around RcppArmadillo::sample() to then call in R won’t get you much of a performance boost. However, if you need to repeatedly call sample(), then calling a...

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An accept-reject sampler using RcppArmadillo::sample()

May 8, 2013
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An accept-reject sampler using RcppArmadillo::sample()

The recently added RcppArmadillo::sample() functionality provides the same algorithm used in R’s sample() to Rcpp-level code. Because R’s own sample() is written in C with minimal work done in R, writing a wrapper around RcppArmadillo::sample() to then call in R won’t get you much of a performance boost. However, if you need to repeatedly call sample(), then calling a...

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Gambler’s Run With Shiny

May 8, 2013
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Gambler’s Run With Shiny

I finally had an opportunity to play with Shiny, and I am very impressed. I have created a Github Project so head over there for the source code. There are a number of ways to distribute Shiny apps. If you are running R (and mostly likely you are if you are reading this), you can download and...

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heatmaps with p-values (2)… coloured according to odds ratio

May 7, 2013
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heatmaps with p-values (2)… coloured according to odds ratio

I like heatplots with p-values -or frequencies, or whatever-. Not very conclusive, but pretty anyway. And when talking about graphs, pretty will make our neurons to fire in more interesting ways: neurons like “pretty” graphs. Moreover, observing your data can … Sigue leyendo →

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