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Do you ever see strange lights in the sky? Do you wonder what really goes on in Area 51? Would you like to use your R hacking skills to get to the bottom of the whole UFO conspiracy? Of course, you would! UFO data from infochimps is the focus of a ... [Read more...]

Last week I have updated the ‘qgraph‘ package to version 1.1.0, available on CRAN now. Besides some internal changes (especially the self-loops have been substantially improved) the most important change is the addition of a GUI interface, which can be … Continue reading → [Read more...]

The VIX (volatility index) is a financial index which measures the expectation of the volatility of the stock market index S&P 500 (SPX). The higher is the value of the VIX the higher are the expectations of important variations in the S&P 500 during the next month. Since volatility is ... [Read more...]

There has recently been a lot of discussion of so-called “visually-weighted regression” plots. Folk hero Hadley Wickham suggests that such plots would be easy to implement with ggplot2, and so I have attempted to prove him right. The approa... [Read more...]

I like the idea of having data on school performance, not to directly rank schools—hard, to say the least, at this stage—but because we can start having a look at the factors influencing test results. I imagine the opportunity in … Continue reading → [Read more...]

What is variance targeting in garch estimation?  And what is its effect? Previously Related posts are: A practical introduction to garch modeling Variability of garch estimates garch estimation on impossibly long series The last two of these show the variability of garch estimates on simulated series where we know the ... [Read more...]

It’s Friday night, there’s nothing good on TV, mmm conditions are perfect for shaggin about in R. So I’m an NFL fan, and (shameless plug) avid fan of this NFL podcast. They run their own pickem league which unless users … Continue reading → [Read more...]

First an apology, the links to the Universal Portfolio paper have stopped working.  This is because the personal webpage of Thomas Cover at Stanford has been taken down, but fortunately the content moved elsewhere.  The new link is Universal ... [Read more...]

Today I want to follow up with the Minimum Correlation Algorithm Paper post and show how to incorporate the Minimum Correlation Algorithm into your portfolio construction work flow and also explain why I like the Minimum Correlation Algorithm. First, let’s load the ETF’s data set used in the ... [Read more...]

Learn how Oracle R Enterprise is used to generate new insight and new value to business, answering not only what happened, but why it happened. View this YouTube Oracle Channel video overview desc... [Read more...]

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It’s been quite a while since my last post on Euler problems. Today a visitor post his solution to the second problem nicely, which encouraged me to keep solving these problems. Just for fun! 10! = 10 * 9 * … * 3 * 2 * 1 … Continue reading → [Read more...]

For R beginners, the apply() function seems like a secret doorway into programming bliss. It seems so powerful, and yet, beyond reach. For those just starting out, examples of how to use apply() can really help with the intuition of how to h... [Read more...]

Hi everyone – I just wrote a tutorial on text analysis in R using the tm and wordcloud packages. Thought some of you here might be interested in it: text-analysis-75-925 [Read more...]

Consider our loss-ALAE dataset, and - as in Frees & Valdez (1998) - let us fit a parametric model, in order to price a reinsurance treaty. The dataset is the following, __ library(evd) __ data(lossalae) __ Z=lossalae __ X=Z[,1];Y=Z[,2] ... [Read more...]

Numerically-coded data sequences can exhibit a very wide range of distributional characteristics, including near-Gaussian (historically, the most popular working assumption), strongly asymmetric, light- or heavy-tailed, multi-modal, or discrete (e.g., count data).  In addition, numerically coded values can be effectively categorical, either ordered, or unordered.  A specific example that illustrates ... [Read more...]

I write sloppy R scripts. It is a byproduct of working with a high-level language that allows you to quickly write functional code on the fly (see this post for a nice description of the problem in Python code) and the result of my limited formal training in computer programming. ... [Read more...]

This post is actually a homework I did. The data file contains input use, output, quantities, costs, and prices for total U.S. nondurable manufacturing for 1949-2001. The data are defined as follows: , , , , = Inputs corresponding to capital, labor, energy, materials, and purchased services, = represents total output, = respective quantity indexes, = ... [Read more...]

Another full day spent working with Jean-Michel Marin on the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) and the remaining hierarchical Bayes chapter… I have reread and completed the regression and GLM chapters, sent to very friendly colleagues for a last round of comments. Now, ... [Read more...]