# Monthly Archives: January 2014

## Comparing multiple (g)lm in one graph #rstats

January 29, 2014
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It’s been a while since a user of my plotting-functions asked whether it would be possible to compare multiple (generalized) linear models in one graph (see comment). While it is already possible to compare multiple models as table output, I now managed to build a function that plots several (g)lm-objects in a single ggplot-graph. The

## Data mining with R course in the Netherlands taught by Luis Torgo

January 29, 2014
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In the course of this year, Dr. Luis Torgo will teach a Data Mining with R course together with the DIKW Academy in Nieuwegein, The Netherlands. Dr. Torgo is an Associate Professor at the department of Computer Science at the… See more ›

## Inference for AR(p) Time Series

January 28, 2014
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$Y_t =\varphi_1 Y_{t-1}+\varphi_2 Y_{t-2}+\varepsilon_t$

Consider a (stationary) autoregressive process, say of order 2, for some white noise with variance . Here is a code to generate such a process, > phi1=.25 > phi2=.7 > n=1000 > set.seed(1) > e=rnorm(n) > Z=rep(0,n) > for(t in 3:n) Z=phi1*Z+phi2*Z+e > Z=Z > n=length(Z) > plot(Z,type="l") Here, we have to estimate two sets of parameters: the autoregressive...

## Lies, Damn Lies, “Data Journalism” and Charts That Don’t Start at 0

January 28, 2014
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This tweet by @moorehn (who usually is a superb economic journalist) really bugged me: Alarming chart of employment for people between 25 and 54. It's like a ski jump. #SOTUecon pic.twitter.com/KNGYmwI88C— Heidi N. Moore (@moorehn) January 29, 2014 I grabbed the raw data from EPI: (http://www.epi.org/files/2012/data-swa/jobs-data/Employment%20to%20population%20ratio%20(EPOPs).xls) and properly started the graph at 0 for the

## cut, baby, cut!

January 28, 2014
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At MCMSki IV, I attended (and chaired) a session where Martyn Plummer presented some developments on cut models. As I was not sure I had gotten the idea [although this happened to be one of those few sessions where

## Time series data in R

January 28, 2014
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There is no shortage of time series data available on the web for use in student projects, or self-learning, or to test out new forecasting algorithms. It is now relatively easy to access these data sets directly in R. M Competition data The 1001 series from the M-competition and the 3003 series from the M3-competition are available as part...

## Binomial testing with buttered toast

January 28, 2014
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Rasmus' post of last week on binomial testing made me think about p-values and testing again. In my head I was tossing coins, thinking about gender diversity and toast. The toast and tossing a buttered toast in particular was the most helpful thought experiment, as I didn't have a fixed opinion on the probabilities for a toast to...

## Analyzing Sleep with Sleep Cycle App and R

January 28, 2014
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I have been tracking my sleep for almost two years now using my Fitbit. I started with the Fitbit Ultra and then moved on the the Fitbit One after it came out. In October 2013 I found out about the Sleep Cycle (Link) app for the iPhone. For weeks, Sleep Cycle was listed as the … Continue reading...

## Ryan Peek on Creating Shiny Apps

January 28, 2014
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Yesterday at the Davis R User’s Group1, Ryan Peek gave a talk about using the shiny package to create interactive web apps with R. Here are his slides. Ryan includes a bunch of links to examples and tutorials, as well as his own thermohydrographs app: Thanks to Revolution Analytics for another year of...

## Context Matters When Modeling Human Judgment and Choice

January 28, 2014
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Herbert Simon was succinct when he argued that judgment and choice "is shaped by a scissor whose two blades are the structure of the task environment and the computational capabilities of the actor" (Simon, 1990, p.7). As a marketing researcher, I take...