Monthly Archives: October 2012

Stan for Bayesian Analysis

October 23, 2012
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Stan for Bayesian Analysis

Bayesian analysis has been growing in popularity among ecologists recently, largely due to accessible books such as Models for Ecological Data: An Introduction, Introduction to WinBUGS for Ecologists, and Bayesian Methods for Ecology. Most ecologists with limited programming background have … Continue reading →

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RStudio training

October 23, 2012
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RStudio training

At RStudio, we want you to be effective R users. As well as creating great software, we want to make it easier for you to master R. To this end, we’re very happy to announce our new training offerings. We’re kicking off with two public courses: Effective data visualisation and reports and reproducible research in

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Machine learning for hackers

October 23, 2012
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Machine learning for hackers

Which way do you prefer to learn a new material – deep theoretical background first and practice later or do you like to break things in order to fix them? If latter is your way of learning things, then most likely you will enjoy Machine Learning for Hackers. The book has chapters on machine learning

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Two Talks on Data Science, Big Data and R

October 23, 2012
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On Thursday next week (November 1), I'll be giving a new webinar on the topic of Big Data, Data Science and R. Titled "The Rise of Data Science in the Age of Big Data Analytics: Why Data Distillation and Machine Learning Aren’t Enough", this is a provocative look at why data scientists cannot be replaced by technology, and why...

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Multiple levelplots with title and subtitle in R

October 23, 2012
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Multiple levelplots with title and subtitle in R

I had quite a fight with R to put multiple levelplots with a shared title and subtite on the same chart, so I thought I put a PoC code here: library(lattice)m col.l plot.new()par(mfrow=c(2,2), oma=c(2,0,2,0))print(levelplot(m, col.regions=col.l, main="L1"), split=c(1, 1, 2, 2)) print(levelplot(m, col.regions=col.l, main="L2"), split=c(1, 2, 2, 2), newpage=FALSE)print(levelplot(m, col.regions=col.l, main="L3"), split=c(2, 1, 2, 2), newpage=FALSE)print(levelplot(m, col.regions=col.l, main="L4"), split=c(2,...

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Bayes for President!

October 23, 2012
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Bayes for President!

I couldn't resist getting sucked into the hype associated with the US election and debates, and so I thought I had a little fun of my own and played around a bit with the numbers. [OK: you may disagree with the definition of "fun" $-$ but then again, i...

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analyze the general social survey (gss) with r

October 23, 2012
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the general social survey (gss) has served as america's mood ring since 1972.  data-driven social scientists can compare political beliefs by demography, look at attitude trends, make emile durkheim and max weber (pronounced durk-veber) proud.&nbs...

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Benchmarking matrix creation

October 23, 2012
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Benchmarking matrix creation

Sometimes it is useful to take a vector, or one column/row of a matrix, and build a new matrix of identical copies of that vector. There are lots of different ways to do this, but I just discovered a new, and very straightforward way to do this with m...

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The basics of Value at Risk and Expected Shortfall

October 23, 2012
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The basics of Value at Risk and Expected Shortfall

Value at Risk and Expected Shortfall are common risk measures.  Here is a quick explanation. Ingredients The first two ingredients are each a number: The time horizon — how many days do we look ahead? The probability level — how far in the tail are we looking? Ingredient number 3 is a prediction distribution of … Continue reading...

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On Volatility Proxy

October 23, 2012
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On Volatility Proxy

Volatility is unobserved. Hence we need to use observed quantity as a proxy. Every once in a while I still see people using squared daily return as a proxy. However, there is ample evidence that it is a bad one. … Continue reading →

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