2785 search results for "ggplot"

ggtern 1.0.3.1 on CRAN

February 1, 2014
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An update to ggtern, version 1.0.3.1, is now available on CRAN! This version includes a number of updates and functionality, which can be summarized below: Inclusion of USDA Soil Classification Data, accessed by: data(USDA) Creation of New geometries for ternary errorbars, ie, geom_errorbarT, geom_errorbarL and geom_errorbarR Creation of convenience functions (theme_showtitles and theme_hidetitles) for hiding… The post ggtern...

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Know India through Visualisations – 1

February 1, 2014
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Know India through Visualisations – 1

I'm going to produce just a couple of charts, a teaser of sorts in this post. In the forthcoming posts I'll dig deeper.I was amazed with the existing list of R packages to work with spatial data, without needing to get into much of the technical detail...

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ShareLaTeX now supports knitr

January 31, 2014
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ShareLaTeX (click here to register a free account) is a wonderful and reliable on-line editor for writing and compiling LaTeX documents “in the cloud” as well as working together in real-time (imagine Google Docs supporting LaTeX => you get ShareLaTeX).…Read more ›

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Comparing multiple (g)lm in one graph #rstats

January 29, 2014
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Comparing multiple (g)lm in one graph #rstats

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

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

January 28, 2014
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Lies, Damn Lies, “Data Journalism” and Charts That Don’t Start at 0

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

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Quantitative Finance Applications in R – 3: Plotting xts Time Series

January 28, 2014
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Quantitative Finance Applications in R – 3: Plotting xts Time Series

by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction and Data Setup Last time, we included a couple of examples of plotting a single xts time series using the plot(.) function (ie, said function included in the xts package). Today, we’ll look at some quick and easy methods for plotting overlays of multiple xts time series in a single...

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Expected overestimation of Cohen’s d under publication bias

January 27, 2014
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Expected overestimation of Cohen’s d under publication bias

Earlier this week I read this article about “Why Publishing Everything Is More Effective than Selective Publishing of Statistically Significant Results” by Mercal et al (2014). The authors simulated different meta-analytic scenarios and came to the conclusion that publishing everything is more effective for the scientific collective. This got me thinking about...

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Expected overestimation of Cohen’s d under publication bias

January 27, 2014
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Expected overestimation of Cohen’s d under publication bias

In this post I will use the theoretical and empirical sampling distribution of Cohen's d to show the expected overestimation due to selective publishing. I will look at the overestimation for various sample sizes when the population effect is 0, 0.2, 0.5 and 0.8. The conclusion is that you should be weary of effect sizes from small samples, and...

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An idiot learns Bayesian analysis: Part 1

January 25, 2014
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An idiot learns Bayesian analysis: Part 1

I've done a dreadful job of reading The Theory That Would Not Die, but several weeks ago I somehow managed to read the appendix. Here the author gives a short explanation of Bayes' theorem using statistics related to breast cancer and mammogram results. This is the same real world example (one of several) used by

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Shoot The Heart With Monte Carlo

January 23, 2014
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Shoot The Heart With Monte Carlo

The heart has its reasons which reason knows not (Blaise Pascal) You only need two functions to draw a heart mathematically. The upper part is generated by (1-(|x|-1)2)1/2 and the lower one by acos(1-|x|)-PI. Here is how this heart is: Whats the area of this heart? It’s easy: integrating heart.up(x)-heart.dw(x) between -2 and 2 and

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