367 search results for "boxplot"

Study of a plot

December 3, 2014
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Study of a plot

I began to think on a nice way of plotting campaign expenditures in a paper I'm working on. I thought this would be something like the following--simple but meaningful even when there are outliers in both tails. Though I like the seniors Tukey's boxplot and scatter plots, I had already used them the last time … Read More...

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Visualizing Historical & Most-likely First Snowfall Dates for U.S. Regions

November 26, 2014
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Visualizing Historical & Most-likely First Snowfall Dates for U.S. Regions

UPDATE: You can now run this as a local Shiny app by entering shiny::runGist("95ec24c1b0cb433a76a5", launch.browser=TRUE) at an R prompt (provided all the dependent libraries (below) are installed) or use it interactively over at Shiny Apps. The impending arrival of the first real snowfall of the year in my part of Maine got me curious about

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Visualization of probabilistic forecasts

November 21, 2014
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Visualization of probabilistic forecasts

This week my research group discussed Adrian Raftery’s recent paper on “Use and Communication of Probabilistic Forecasts” which provides a fascinating but brief survey of some of his work on modelling and communicating uncertain futures. Coincidentally, today I was also sent a copy of David Spiegelhalter’s paper on “Visualizing Uncertainty About the Future”. Both are

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Bioinformatics journals: time from submission to acceptance, revisited

October 13, 2014
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Bioinformatics journals: time from submission to acceptance, revisited

Before we start: yes, we’ve been here before. There was the Biostars question “Calculating Time From Submission To Publication / Degree Of Burden In Submitting A Paper.” That gave rise to Pierre’s excellent blog post and code + data on Figshare. So why are we here again? 1. It’s been a couple of years. 2.

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ggvis 0.4

October 13, 2014
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ggvis 0.4

ggvis 0.4 is now available on CRAN. You can install it with: install.packages("ggvis") The major features of this release are: Boxplots, with layer_boxplots() chickwts %>% ggvis(~feed, ~weight) %>% layer_boxplots() Better stability when errors occur. Better handling of empty data and malformed data. More consistent handling of data in compute pipeline functions. Because of these changes,

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An Intro to Models and Generalized Linear Models in R

October 13, 2014
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An Intro to Models and Generalized Linear Models in R

By Chris Campbell – Senior Consultant, UK. For many types of data, we have made a measurement of some variable that looks normally distributed. The middle value is the most likely, most values are similar to the middle value, and a … Continue reading →

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Multiple Tests, an Introduction

September 24, 2014
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Multiple Tests, an Introduction

Last week, a student asked me about multiple tests. More precisely, she ran an experience over – say – 20 weeks, with the same cohort of – say – 100 patients. An we observe some size=100 nb=20 set.seed(1) X=matrix(rnorm(size*nb),size,nb) (here, I just generate some fake data). I can visualize some trajectories, over the 20 weeks, library(RColorBrewer) cl1=brewer.pal(12,"Set3") cl2=brewer.pal(8,"Set2") cl=c(cl1,cl2)...

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“Do You Want to Steal a Snowman?” – A Look (with R) At TorrentFreak’s Top 10 PiRated Movies List #TLAPD

September 18, 2014
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“Do You Want to Steal a Snowman?” – A Look (with R) At TorrentFreak’s Top 10 PiRated Movies List #TLAPD

We leave the Jolly Roger behind this year and turn our piRate spyglass towards the digital seas and take a look at piRated movies as seen through the lens of TorrentFreak. The seasoned seadogs who pilot that ship have been doing a weekly “Top 10 Pirated Movies of the Week” post since early 2013, and...

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Comparing machine learning models in R

September 18, 2014
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Comparing machine learning models in R

by Joseph Rickert While preparing for the DataWeek R Bootcamp that I conducted this week I came across the following gem. This code, based directly on a Max Kuhn presentation of a couple years back, compares the efficacy of two machine learning models on a training data set. #----------------------------------------- # SET UP THE PARAMETER SPACE SEARCH GRID ctrl <-...

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R version of “An exploratory technique for visualizing the distributions of 100 variables:”

September 10, 2014
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R version of “An exploratory technique for visualizing the distributions of 100 variables:”

Rick Wicklin (@RickWicklin) made a recent post to the SAS blog on An exploratory technique for visualizing the distributions of 100 variables. It’s a very succinct tutorial on both the power of boxplots and how to make them in SAS (of course). I’m not one to let R be “out-boxed”, so I threw together a

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