Monthly Archives: January 2014

Building Affine Transformation Fractals With R

January 5, 2014
By
Building Affine Transformation Fractals With R

Clouds are not spheres, mountains are not cones, coastlines are not circles and bark is not smooth, nor does lightning travel in a straight line (Benoit Maldelbrot) Fractals are beautiful, hypnotics, mysterious. Cantor set has as many points as the real number line but has zero measure. After 100 steps, the Koch curve created from

Read more »

Validating R-Backtesting frameworks against Metatrader 4 with 99% tick accuracy

January 5, 2014
By
Validating R-Backtesting frameworks against Metatrader 4 with 99% tick accuracy

The primary objective here is to make sure the framework I use in R to backtest strategies delivers similar results to that of MT4, most specifically to 99% tick accuracy MT4 backtesting. Why the 99% tick accuracy …. because it’s … Continue reading →

Read more »

Cran2deb4ubuntu: An Update for 2014

January 5, 2014
By

I have been a little quiet on the update front for the past few months, so I thought I would give a quick update as 2014 begins. Between increased responsibilities at work (pseudo-department chair) and some family health issues, work on cran2deb4ubunt...

Read more »

Bayesian PCA

January 5, 2014
By

Authors: Jan Smycka, Petr Keil This post introduces experimental R package bPCA which we developed with Jan Smycka, who actually came with the idea. We do not guarantee the very idea to be correct and there certainly are bugs – we invite anyone to show us wrong, or to contribute. … Continue reading →

Read more »

ggtern 1.0.2.0 on CRAN

January 4, 2014
By

An update to ggtern, version 1.0.2.0, is now available on CRAN! This version includes a number of updates, and, additional functionality, which can be summarized below: Better Documentation Theme commands were brought back inline with the ggplot2 format, for example, theme_tern_bw() has been superceded by theme_bw() as per ggplot2 The default theme (theme_gray()) was modified… The post ggtern...

Read more »

Analyse your bank statements using R

January 4, 2014
By
Analyse your bank statements using R

Online banking has made reviewing statements and transferring money more convenient than ever before, but most still rely on external methods for looking at their personal finances. However, many banks will happily give you access to long-term transaction logs, and … Continue reading →

Read more »

Calibration Affirmation

January 4, 2014
By
Calibration Affirmation

In the book, we discuss the notion of a probability model being "well calibrated". There are many different mathematical techniques that classification models use to produce class probabilities. Some of values are "probability-like" in that they are between zero and one and sum to one. This doesn't necessarily mean that the probability estimates are consistent with the true event...

Read more »

Relenium, Selenium for R. A new tool for webscraping.

January 4, 2014
By
Relenium, Selenium for R. A new tool for webscraping.

  Two members of the RugBcn  have developed a package for R that ease the path for webscraping . Among the current packages, we highlight the well known RCurl and XML packages. Both are enough for most situations, but they have a limitation dealing with situations where there is some javascript between the user and the information. For instance when

Read more »

Le Monde puzzle 847 in Julia

January 4, 2014
By

This week I wanted to play around with Julia and exporting the results. I found http://xianblog.wordpress.com/2013/12/29/le-monde-puzzle-847/ to be just the right size to play around with. CodeA function to check if a triplet has the desired property In : function lemonde847(xx) a=,2] b=,8] c=,4] sum(kron(c,kron(a,b)))endOut:lemonde847 (generic function with 1 method)Just a check -...

Read more »

Detecting a Time Series Change Point

January 4, 2014
By
Detecting a Time Series Change Point

In this example we will detect the change point in a time series of counts using Bayesian methodology. A natural solution to this problem utilizes a Gibbs sampler. We’ll first implement the sampler in R naively, then create a vectorized R implementation, and lastly create an implementation of the sampler using Rcpp and RcppArmadillo. We will compare these implementations...

Read more »

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)