# 2875 search results for "twitteR"

## Cycles in finite populations: A reproducible seminar in three acts

November 1, 2011
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For this years Halloween I presented the mathematical biology seminar at the Centre for Mathematical Biology. Here is the title and the abstract… Cycles in finite populations: a reproducible seminar in three acts Many natural populations exhibit cyclic fluctuations. Explaining the underlying … Continue reading →

## Selecting statistics for ABC model choice [R code]

November 1, 2011
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As supplementary material to the ABC paper we just arXived, here is the R code I used to produce the Bayes factor comparisons between summary statistics in the normal versus Laplace example. (Warning: running the R code takes a while!) Filed under: R, Statistics, University life Tagged: ABC, Bayesian model choice, Laplace distribution, R, summary

## Use case: combining taxize and rgbif

November 1, 2011
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Sure thing….this is just the sort of thing for which rOpenSci is being built. A colleague of mine recently saw our packages in development and thought, “Hey, that could totally make my life easier.”   What was made easier you ask?   This was his situation: He had a list of ca. 1200 species of

## Code Optimization: One R Problem, Ten Solutions – Now Eleven!

November 1, 2011
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Earlier this year I came across a rather interesting page about optimisation in R from rwiki. The goal was to find the most efficient code to produce strings which follow the pattern below given a single integer input n: From this we can see that the general pattern for n is: It is rather heart

## Minimizing Downside Risk

November 1, 2011
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$Minimizing Downside Risk$

In the Maximum Loss and Mean-Absolute Deviation risk measures, and Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) posts I started the discussion about alternative risk measures we can use to construct efficient frontier. Another alternative risk measure I want to discuss is Downside Risk. In the traditional mean-variance optimization both returns above and

## How Might Data Journalists Show Their Working? Sweave

November 1, 2011
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If part of the role of data journalism is to make transparent the justification behind claims that are, or aren’t, backed up by data, there’s good reason to suppose that the journalists should be able to back up their own data-based claims with evidence about how they made use of the data. Posting links to

## Plotting grouped data vs time with error bars in R

October 31, 2011
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This is my first blog since joining R-bloggers. I’m quite excited to be part of this group and apologize if I bore any experienced R users with my basic blogs for learning R or offend programmers with my inefficient, sloppy … Continue reading →

## Power Tools for Aspiring Data Journalists: R

October 31, 2011
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Picking up on Paul Bradshaw’s post A quick exercise for aspiring data journalists which hints at how you can use Google Spreadsheets to grab – and explore – a mortality dataset highlighted by Ben Goldacre in DIY statistical analysis: experience the thrill of touching real data, I thought I’d describe a quick way of analysing

## Sampling for Monte Carlo simulations with R

October 31, 2011
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$Sampling for Monte Carlo simulations with R$

I've knocked together a quick function for generating efficient Monte Carlo samples. It takes a bit of the legwork out of running Monte Carlo simulations.

## Bayesian ideas and data analysis

October 30, 2011
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Here is another Bayesian textbook that appeared recently. I read it in the past few days and, despite my obvious biases and prejudices, I liked it very much! It has a lot in common (at least in spirit) with our Bayesian Core, which may explain why I feel so benevolent towards Bayesian ideas and