Amy Cuddy: Your body language shapes who you are
Amy Cuddy gives a great talk. Provided me with lots to think about and I will happily confess that I have struck a few power poses (but only after ensuring that I am quite alone)!
Read More →Social links CV.
and a link to my
Public datasets:
Amy Cuddy gives a great talk. Provided me with lots to think about and I will happily confess that I have struck a few power poses (but only after ensuring that I am quite alone)!
Read More →Following up on my recent post about implementing a queue as a reference class, I am going to derive a Priority Queue class.
Read More →I am working on a simulation for an Automatic Repeat-reQuest (ARQ) algorithm. After trying various options, I concluded that I would need an implementation of a queue to make this problem tractable. R does not have a native queue data structure, so this seemed like a good opportunity to implement one and learn something about Reference Classes in the process.
We use setRefClass() to create a generator function which will create objects of the Queue class.
Read More →According to Wikipedia, an iterator is “an object that enables a programmer to traverse a container”. A collection of items (stashed in a container) can be thought of as being “iterable” if there is a logical progression from one element to the next (so a list is iterable, while a set is not). An iterator is then an object for moving through the container, one item at a time.
Iterators are a fundamental part of contemporary Python programming, where they form the basis for loops, list comprehensions and generator expressions. Iterators facilitate navigation of container classes in the C++ Standard Template Library (STL). They are also to be found in C#, Java, Scala, Matlab, PHP and Ruby.
Read More →A short while ago I was contracted to write a short piece entitled “Introduction to Fractals”. Admittedly it is hard to do justice to the topic in less than 1000 words.
Read More →In my previous post about estimating the Percolation Threshold on a square lattice, I only considered flow from a given cell to its four nearest neighbours. It is a relatively simple matter to extend the recursive flow algorithm to include other configurations as well.
Malarz and Galam (2005) considered the problem of percolation on a square lattice for various ranges of neighbor links. Below is their illustration of (a) nearest neighbour “NN” and (b) next-nearest neighbour “NNN” links.
Read More →Manfred Schroeder touches on the topic of percolation a number of times in his encyclopaedic book on fractals (Schroeder, M. (1991) Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise. Percolation has numerous practical applications, the most interesting of which (from my perspective) is the flow of hot water through ground coffee!
Read More →I recently enjoyed reading O’Hara, R. B., & Kotze, D. J. (2010). Do not log-transform count data. Methods in Ecology and Evolution, 1(2), 118–122. doi:10.1111/j.2041-210X.2010.00021.x.
Read More →I need to mount a directory from my laptop on my desktop machine using sshfs. At first I was not making the mount terribly regularly, so I did it manually each time that I needed it. However, the frequency increased over time and I was eventually mounting it every day (or multiple times during the course of a day!). This was a perfect opportunity to employ some automation.
Read More →Some years ago I allowed myself to accept a challenge to read the Top 100 Novels of All Time (complete list here). This list was put together by Richard Lacayo and Lev Grossman at Time Magazine.
To start with I could tick off a number of books that I had already read. That left me with around 75 books outstanding. I knuckled down. The Lord of the Rings had been on my reading list for a number of years, so this was my first project. A little unfair for this trilogy to count as just one book… but I consumed it with gusto! One down. Other books followed. They were also great reads. And then I hit a couple of books that were just, well, to put it plainly, heavy going. I am sure that they were great books and my lack of enjoyment was entirely a reflection on me and not the quality of the books. No doubt I learned a lot from reading them. But it was hard work! At this stage it occurred to me that the book list was constructed from a rather specific perspective of what constituted a great book. A perspective which is quite different from my own. I had to admit defeat: my literary tastes will have to mature a bit before I attack this list again!
Read More →The logs generated by expert advisors and indicators when running live on MetaTrader are displayed in the Experts tab at the bottom of the terminal window. Sometimes it is more convenient to analyse these logs offline (especially since the order of the records in the terminal runs in a rather counter-intuitive bottom-to-top order!). However, because writing to the log files is buffered, there can be a delay before what you see in the terminal is actually written to disk.
Read More →In my previous post I used the tm
package to do some simple text mining on the Complete Works of William Shakespeare. Today I am taking some of those results and using them to generate word clusters.
Time zones on MetaTrader can be slightly confusing. Two specific time zones are important:
And these need not be the same.
Read More →I am starting a new project that will require some serious text mining. In the interests of bringing myself up to speed on the {tm}
package, I thought I would apply it to the Complete Works of William Shakespeare and just see what falls out.
The first order of business was getting my hands on all that text. Fortunately it is available from a number of sources. I chose to use Project Gutenberg.
Read More →A client came to me with some conformance data. She was having a hard time making sense of it in a spreadsheet. I had a look at a couple of ways of presenting it that would bring out the important points.
The data came as a spreadsheet with multiple sheets. Each of the sheets had a slightly different format, so the easiest thing to do was to save each one as a CSV file and then import them individually into R.
Read More →Writing code from scratch to do parallel computations can be rather tricky. However, the packages providing parallel facilities in R make it remarkably easy. One such package is foreach. I am going to document my trail of discovery with foreach, which began some time ago, but has really come into fruition over the last few weeks.
First we need a reproducible example. Preferably something which is numerically intensive.
max.eig <- function(N, sigma) {
d <- matrix(rnorm(N**2, sd = sigma), nrow = N)
#
E <- eigen(d)$values
#
abs(E)[[1]]
}
This function generates a square matrix of uniformly distributed random numbers, finds the corresponding (complex) eigenvalues and then selects the eigenvalue with the largest modulus. The dimensions of the matrix and the standard deviation of the random numbers are given as input parameters.
Read More →Maximum-Likelihood Estimation (MLE) is a statistical technique for estimating model parameters. It basically sets out to answer the question: what model parameters are most likely to characterise a given set of data? First you need to select a model for the data. And the model must have one or more (unknown) parameters. As the name implies, MLE proceeds to maximise a likelihood function, which in turn maximises the agreement between the model and the data.
Read More →Following up on my previous post as a result of an excellent suggestion from Andrej Spiess. The data are indeed very heteroscedastic! Andrej suggested that an alternative way to attack this problem would be to use weighted correlation with weights being the inverse of the measurement variance.
Read More →A week or so ago a colleague of mine asked if I knew how to calculate correlations for data with uncertainties. Now, if we are going to be honest, then all data should have some level of experimental or measurement error. However, I suspect that in the majority of cases these uncertainties are ignored when considering correlations. To what degree are uncertainties important? A moment’s thought would suggest that if the uncertainties are large enough then they should have a rather significant effect on correlation, or more properly, the uncertainty measure associated with the correlation. What is the best (or at least correct) way to proceed? Somewhat surprisingly a quick Google search did not turn up anything too helpful.
Read More →Debugging an indicator or expert advisor (EA) can be a tricky business. Especially when you are doing the debugging remotely. I write my MQL code to include copious amounts of debugging information to log files. The contents of these log files can be used to diagnose any problems. This articles tells you where you can find those files.
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