Monthly Archives: February 2017

The R Formula Method: The Bad Parts

February 28, 2017
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The R Formula Method: The Bad Parts

R’s model formula infrastructure was discussed in my previous post. Despite the elegance and convenience of the formula method, there are some aspects that are limiting. Limitations to Extensibility The model formula interface does have some limitations: It can be kludgy with many operations on many variables (e.g., log transforming 50 variables via a formula without using paste) The predvars...

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Copying tables from R to Outlook

February 28, 2017
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Copying tables from R to Outlook

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

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testing R code [book review]

February 28, 2017
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testing R code [book review]

When I saw this title among the CRC Press novelties, I immediately ordered it as I though it fairly exciting. Now that I have gone through the book, the excitement has died. Maybe faster than need be as I read it while being stuck in a soulless Schipol airport and missing the only ice-climbing opportunity

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US Babyname Collisions 1880-2014

February 28, 2017
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US Babyname Collisions 1880-2014

Abstract We use US Social Security Administration data to compute the probability of a name clash in a class of year-YYYY born kids during the years 1880-2014. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The markdown+Rknitr source code of this blog is available under a

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

February 28, 2017
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A (much belated) update to plotting Kaplan-Meier curves in the tidyverse

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 these attempts to create a much more stable and feature-rich

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Forecasting gentrification in city neighborhoods, with R

February 28, 2017
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Forecasting gentrification in city neighborhoods, with R

If you've lived in a big city, you're likely familiar with the impact of gentrification. For longtime residents of a neighbourhood, it can represent a decline in the culture and vibrancy of your community; for recent or prospective residents, it can represent a financial opportunity in rising home prices. For those that live in a gentrifying neighbourhood, it's one...

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How to create correlation network plots with corrr and ggraph (and which countries drink like Australia)

February 28, 2017
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How to create correlation network plots with corrr and ggraph (and which countries drink like Australia)

@drsimonj here to show you how to use ggraph and corrr to create correlation network plots like these:  ggraph and corrr The ggraph package by Thomas Lin Pedersen, has just been published on CRAN and it’s so hot right now! What does it do? “ggraph is an extension of ggplot2...

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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 uncorrelated, normally distributed, etc.). The...

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forecast 8.0

February 28, 2017
By
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

Read more »

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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