Monthly Archives: February 2017

forecast 8.0

February 28, 2017
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forecast 8.0

In what is now a roughly annual event, the forecast package has been updated on CRAN with a new version, this time 8.0. A few of the more important new features are described below. Check residuals A common task when building forecasting models is to check that the residuals satisfy some assumptions (that they are

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How to annotate a plot in ggplot2

February 28, 2017
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How to annotate a plot in ggplot2

After you master the basics of R and ggplot2, you need to learn the little details. A great example of this is plot annotation. Adding little details like plot annotations help you communicate more clearly and "tell a story" with your plots. The post How to annotate a plot in ggplot2 appeared first on SHARP SIGHT LABS.

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A (much belated) update to plotting Kaplan-Meier curves in the tidyverse

February 27, 2017
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One of the most popular posts on this blog has been my attempt to create Kaplan-Meier plots with an aligned table of persons-at-risk below it under the ggplot paradigm. That post was last updated 3 years ago. In the interim, Chris Dardis has built upon...

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Copying tables from R to Outlook

February 27, 2017
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I work in an ecosystem that uses Outlook for e-mail. When I have to communicate results with collaborators one of the most frequent tasks I face is to take a tabular output in R (either a summary table or some sort of tabular output) and send it to collaborators in Outlook. One method is certainly to export the table...

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A glance at R-bloggers Twitter feed

February 27, 2017
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A glance at R-bloggers Twitter feed

It’s the second time I write a post about the blog aggregator R-bloggers, probably because I’m all about R blogs now that I have one. My husband says my posts are so meta. My first post was about R blogs names, in this one I shall focus on the last...

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A glance at R-bloggers Twitter feed

February 27, 2017
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A glance at R-bloggers Twitter feed

It’s the second time I write a post about the blog aggregator R-bloggers, probably because I’m all about R blogs now that I have one. My husband says my posts are so meta. My first post was about R blogs names, in this one I shall focus on the last...

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Make your R simulation models 20 times faster

February 27, 2017
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Make your R simulation models  20 times faster

Make your R simulation models 20 times faster R can be frustratingly slow if you use its loops. However, you can speed it up significantly (e.g. 20 times!) using the Rcpp package. That could turn a day long simulation into an hour long simulation. I ...

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ggedit 0.1.1: Shiny module to interactvely edit ggplots within Shiny applications

February 27, 2017
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ggedit is a package that lets users interactively edit ggplot layer and theme aesthetics. In a previous post we showed you how to use it in a collaborative workflow using standard R scripts. More importantly, we highlighted that ggedit outputs to the user, after editing, updated: gg plots, layers, scales and themes as both self-contained … Continue reading ggedit...

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ggraph: ggplot for graphs

February 27, 2017
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ggraph: ggplot for graphs

A graph, a collection of nodes connected by edges, is just data. Whether it's a social network (where nodes are people, and edges are friend relationships), or a decision tree (where nodes are branch criteria or values, and edges decisions), the nature of the graph is easily represented in a data object. It might be represented as a matrix...

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Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart

February 27, 2017
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Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart

Last week, I introduced how to run machine learning applications on Spark from within R, using the sparklyr package. This week, I am showing how to build feed-forward deep neural networks or multilayer perceptrons. The models in this example are built ...

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