Last month I joined Gregory Piatetsky (KDnuggets editor) for a webinar presentation Data Science: Not Just for Big Data, hosted by Kalido. In my portion of the prentation (you can see my slides below), I wanted to react to the Big Data focus which is so much a part of ... [Read more...]

First of all this text is not just about an intuitive perspective on the beta distribution but at least as much about the idea of looking behind a measured empirical probability and thinking of it as a product of chance itself. … Continue reading → The post An intuitive interpretation of the ... [Read more...]

After seeing the announcement by @lauraegerdal of the SEC’s use of dygraphs to visualize market structure, I was inspired to experiment more with the great dygraphs + rCharts.  I really wanted to see how responsive dygraphs would be with a fairly large dataset.  Some Kenneth French US Industry data seemed ... [Read more...]

Quandl has indexed millions of time-series datasets from over 400 sources. All of Quandl’s datasets are open and free. This is great news but before performing any backtest using Quandl data, I want to compare it with a trusted source: Bloomberg for the purpose of this post. I will focus ... [Read more...]

Principal component analysis(PCA) is one of the classical methods in multivariate statistics. In addition, it is now widely used as a way to implement data-processing and dimension-reduction. Besides statistics, there are numerous applications about PCA in engineering, biology, and so on. There are two main optimal properties of PCA,  ... [Read more...]

Debugging code in R R provides several built in features for stepping through code for analyzing and debugging purposes. As an example you can examine variables during the execution of a script. Amongst others you can use the function debug(): After executing lines 8 and 9 you can stepwise inspect what foo() ... [Read more...]

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This post shares the video from the talk presented in November 2013 by Alec Stephenson providing an introduction to R shiny at Melbourne R Users. R Shiny, from the people behind R Studio, allows you to quickly and easily build … Continue reading → [Read more...]

Say you have a dataset, where each row has a date or time, and something is recorded for that date and time. If each row is a unique date - great! If not, you may have rows with the same date, and you have to combine records for the same ... [Read more...]

In my last post I said I wasn’t going to write anymore about neural networks (i.e., multilayer feedforward perceptron, supervised ANN, etc.). That was a lie. I’ve received several requests to update the neural network plotting function described in the original post. As previously explained, R does ... [Read more...]

by Joseph Rickert This past June, the Human Rights Data Analysis Group (HRDAG), a San Francisco based non-profit organization, released its report: “Updated Statistical Analysis of Documentation of Killings in the Syrian Arab Republic”. The report is grim reading, but it represents the necessary, rational work the needs to be ... [Read more...]

Very often people report p-values for linear regression estimates after performing variable selection step. Here is a simple simulation that shows that such a procedure might lead to wrong calibration of such tests.Consider a simple data generating pro... [Read more...]

Advanced R programming topics Similarly as last year, BNOSAC is offering the short course on 'Advanced R programming topics' at the Leuven Statistics Research Center (Belgium).  The course is now part of FLAMES (Flanders Training Network for Methodology and Statistics) and can be found here http://www.flames-statistics.eu/training/... [Read more...]

Sixth Torino R net meeting on 21 Nov 2013, Campus Luigi Einaudi, Università degli Studi di Torino, will have three presentations The importance of R in agrometeorology: a case study, Federico Spanna, Regione Piemonte Settore Fitosanitario; Claudio Cassardo, Università di Torino Dipartimento … Continue reading → [Read more...]

Bayesian Essentials with R is now available both as an e-book and as a hardcover book on amazon.com!Filed under: Books, R, Statistics, University life Tagged: Bayesian Core, Bayesian Essentials with R, e-book, Jean-Michel Marin, R, Springer-Verlag [Read more...]

Some time ago, since I was able to use R by myself, have found some fellows and other people who wanted to learn R as well. Then I pointed them to help pages, to CRAN repositories… but in some cases … Sigue leyendo → [Read more...]

I am currently trying to understand how to reduce the memory used by mclapply. This function is rather complicated and others have explained the differences versus parLapply (A_Skelton73, 2013; lockedoff, 2012 ) and also made it clear that in mclapply each job does not know if the others are running out of ... [Read more...]

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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 ... [Read more...]

A palindrome is a word, phrase, number, or other sequence of symbols or elements, whose meaning may be interpreted the same way in either forward or reverse direction. The famous palindrome - "able was i ere i saw elba" is attributed to  Napoleo... [Read more...]