Monthly Archives: July 2014

Hit and run. Think Bayes!

July 29, 2014
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Hit and run. Think Bayes!

At the R in Insurance conference Arthur Charpentier gave a great keynote talk on Bayesian modelling in R. Bayes' theorem on conditional probabilities is strikingly simple, yet incredibly thought provoking. Here is an example from Daniel Kahneman to test your intuition. But first I have to start with Bayes' theorem.Bayes' theoremBayes' theorem states that given...

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analyze the fda adverse event reporting system (faers) with r

July 29, 2014
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doctors prescribe medications for patients all the time.  all the time.  sometimes the results are beneficial, other times the drug has no discernible effect, but occasionally those substances actually cause harm.  since the drug is alre...

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Creating an analysis as a package and vignette

Creating an analysis as a package and vignette Following from my last post, I am going to go step by step through the process I use to generate an analysis as a package vignette. This will be an analysis of the tweets from the 2012 and 2014 ISMB conference (thanks to Neil and Stephen for...

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Volatility Histeresis: A First Attempt

July 28, 2014
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Volatility Histeresis: A First Attempt

So the last time that a FRAMA strategy was tried with price crossovers, the problem was that due to counter-trending … Continue reading →

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Chain Operations: An Interesting Feature in dplyr Package

July 28, 2014
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Chain Operations: An Interesting Feature in dplyr Package

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Scraping information of CRAN packages

July 28, 2014
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(This article is adapted to the latest version of rvest package.) In my previous post, I demonstrated how we can scrape online data using existing packages. In this post, I will take it a bit further: I will scrape more information of CRAN packages since each of them also has a web page like this. More specifically,...

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Data Caching

July 28, 2014
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Data caching is not new. It is often necessary to save intermediate data files when the process of loading and/or manipulating data takes a considerable amount of time. This problem is further complicated when working with dynamic data that changes regularly. In these situations it often sufficient to use data that is current with in some time frame (e.g....

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Clipping spatial data in R

July 28, 2014
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Clipping spatial data in R

This miniature vignette shows how to clip spatial data based on different spatial objects in R and a ‘bounding box’. Spatial overlays are common in GIS applications and R users are fortunate that the clipping and spatial subsetting functions are mature and fairly fast. We’ll also write a new function called gClip(), that will make clipping by bounding boxes...

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Comment on Sustainability and innovation in staple crop production in the US Midwest

July 28, 2014
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Comment on Sustainability and innovation in staple crop production in the US Midwest

After writing a blog post about the paper “Sustainability and innovation in staple crop production in the US Midwest” I decided to submit a formal comment to the International Journal of Agricultural Sustainability in July 2013, which was published today. As far as I know, Heinemann et al. provided a rebuttal to my comments, which

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jpmml and R (Free Webinar)

July 28, 2014
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jpmml and R (Free Webinar)

This free, global webinar will provide an introduction to jpmml, the world’s leading open-source PMML scoring engine currently being utilized by companies such as Airbnb to rapidly deploy predictive models into production. Webinar Format: – What is PMML? – Building … Continue reading →

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