2248 search results for "MAP"

Pseudo-Random vs. Random Numbers in R

November 25, 2011
By
Pseudo-Random vs. Random Numbers in R

Earlier, I found an interesting post from Bo Allen on pseudo-random vs random numbers, where the author uses a simple bitmap (heat map) to show that the rand function in PHP has a systematic pattern and compares these to truly random numbers obtained from random.org. The post’s results suggest that pseudo-randomness in

Read more »

Pseudo-Random vs. Random Numbers in R

November 25, 2011
By
Pseudo-Random vs. Random Numbers in R

Happy Thanksgiving, everyone. Earlier today, I found an interesting post from Bo Allen on pseudo-random vs random numbers, where the author uses a simple bitmap (heat map) to show that the rand function in PHP has a systematic pattern and compares these to truly random numbers obtained from random.org. The post’s results suggest that pseudo-randomness in PHP is

Read more »

Time series cross-validation 2

November 22, 2011
By
Time series cross-validation 2

In my previous post, I shared a function for parallel time-series cross-validation, based on Rob Hyndman's code.  I thought I'd expand on that example a little bit, and share some additional wrapper functions I wrote to test other forecasting&nbsp...

Read more »

Do we need to deal with ‘big data’ in R?

November 22, 2011
By
Do we need to deal with ‘big data’ in R?

David Smith at the Revolutions blog posted a nice presentation on “big data” (oh, how I dislike that term). It is a nice piece of work and the Revolution guys manage to process a large amount of records, starting with … Continue reading →

Read more »

Sermon Sentiment Analysis

November 22, 2011
By
Sermon Sentiment Analysis

Matt Chandler vs. Mark Driscoll I came across an interesting API from Viral Heat which is capable of “Sentiment Analysis.” This analysis is designed to capture the sentiment of a statement by ranking it on a scale from -1 to 1. For instance, a chipper sentence like “The smell of roses makes me giddy!” is

Read more »

Functional and Parallel time series cross-validation

November 21, 2011
By
Functional and Parallel time series cross-validation

Rob Hyndman has a great post on his blog with example on how to cross-validate a time series model.  The basic concept is simple:  You start with a minimum number of observations (k), and fit a model (e.g. an arima model) to those observation...

Read more »

htmlToText(): Extracting Text from HTML via XPath

November 18, 2011
By
htmlToText(): Extracting Text from HTML via XPath

Converting HTML to plain text usually involves stripping out the HTML tags whilst preserving the most basic of formatting. I wrote a function to do this which works as follows (code can be found on github): The above uses an XPath approach to achieve it’s goal. Another approach would be to use a regular expression. These

Read more »

Black-Litterman Model

November 15, 2011
By
Black-Litterman Model

The Black-Litterman Model was created by Fisher Black and Robert Litterman in 1992 to resolve shortcomings of traditional Markovitz mean-variance asset allocation model. It addresses following two items: Lack of diversification of portfolios on the mean-variance efficient frontier. Instability of portfolios on the mean-variance efficient frontier: small changes in the input assumptions often lead to

Read more »

First attempt at Chess Data Mining

November 15, 2011
By
First attempt at Chess Data Mining

Once you become addicted to chess game analysis, it becomes very easy to swamp yourselves with questions regarding different aspects of the game. Testing out different hypothesis like preference of mobility versus positional advantage requires a bit of manual chess game mining, which could potentially be analyzed using R. With the help of websites like

Read more »

Announcing Revolution R Enterprise 5.0

November 15, 2011
By

We're proud to announce the latest update to the enhanced, commercial-grade distribution of R, Revolution R Enterprise 5.0. With each new release, Revolution R Enterprise adds more capabilities to open-source R, to make R users more productive, to improve performance of R programs, to support Big Data analytics, and to provide servers and APIs for enterprise deployment. New features...

Read more »