R-statistics blog

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• Recent Posts

  • Printing nested tables in R – bridging between the {reshape} and {tables} packages
  • Interactive Graphics with the iplots Package (from “R in Action”)
  • Merging two data.frame objects while preserving the rows’ order
  • Aggregation and Restructuring data (from “R in Action”)
  • Top 20 R posts of 2011 (and some R-bloggers statistics)
  • data.frame objects in R (via “R in Action”)
  • UseR! 2011 slides and videos – on one page
  • edimax EW-7811Un USB wireless – connecting to a network (on ubuntu 11.10)
  • Diagram for a Bernoulli process (using R)
  • The present and future of the R blogosphere (~7 minute video from useR2011)

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• R-bloggers

  • Some new functions I’ve discovered in R
    I’ve been writing a fair amount of R recently and have been going through a good learning period, here are some functions that I’ve discovered (mainly plyr and reshape related) and thought I would share: merge_all is a good way to merge multiple different data frames, rather than multiple merge commands. The key thing is … Continue reading » […]
  • Removing Multibyte Characters from Strings
    I was a bit annoyed by the error when loading a dataset that contains multi-byte characters. R basically just chokes on them. I have not really understood the intricacies of this, but it was basically just an annoyance and since I did not really use these characters in the strings containing them, I just wanted […]
  • hmm: implementation of viterbi algorithm (Durbin, 1998) Part 2
    Previous post presented the problem of dishonest casino that ocassionally uses loaded die. Sequence of the real states is hidden, and we are trying to figure it out just by looking at the observations (symbols). If we apply our implementation to the data in the previous post, we can get the idea how well can […]
  • Visual Summary of #jan25 Twitter Activity
      Last year, I covered a number of the so-called “Twitter protests” in China (#cn220), Iran (#25bahman), and Algeria (#fev12).  Since these protests began in January 2011, the Arab Spring has claimed many members of both ruling and revolting groups … Continue reading → […]
  • Multiple Factor Model – Fundamental Data
    The Multiple Factor Model can be used to decompose returns and calculate risk. Following are some examples of the Multiple Factor Models: The expected returns factor model: Commonality In The Determinants Of Expected Stock Returns by R. Haugen, N. Baker (1996) The expected returns factor model: CSFB Quantitative Research, Alpha Factor Framework on page 11, [ […]
  • Categorizing my expenses
    In order to analyse my expenses, a classification scheme is necessary. I need to identify categories that are meaningful to me. I decided to go with the “Classification of Individual Consumption by Purpose” (COICOP), for three reasons:It is made by... […]
  • Say it in R with "by", "apply" and friends
    Iris versicolor (Source: Wikipedia)R is a language, as Luis Apiolaza pointed out in his recent post. This is absolutely true, and learning a programming language is not much different from learning a foreign language. It takes time and a lot of pr... […]
  • Le Monde puzzle [#755?]
    Le Monde puzzle of last weekend was about sudoku-like matrices. Consider an (n,n) matrix containing the integers from 1 to n². The matrix is “friendly” if the set of the sums of the rows is equal to the set of the sum of the columns. Find examples for n=4,5,6. Why is there no friendly matrix […]
  • hmm: implementation of viterbi algorithm (Durbin, 1998) Part 1
    Example in the mentioned book goes as following – dishonest casino uses two types of dice. Fair one that has equal probability of landing on either side (1/6), and the loaded one with 50% chance for getting 6. Your task is to figure out which die has been used (states) just based on the sequence […]
  • heatmaps: controlling the color representation with set data range
    Often you want to set the fixed colors for particular range of your dataset to be sure that the visual output is correctly represented. This is particularly useful for time series data, where the range or your dataset might drastically change during the course of the simulation. To do that in R, we need to […]