October 2013

The look of verifying data

October 7, 2013 | Pat

Get data that fit before you fit data. Why verify? Garbage in, garbage out. How to verify The example data used here is daily (adjusted) prices of stocks.  By some magic that I’m yet to fathom, market data can be wondrously wrong even without the benefit of the possibility ... [Read more...]

Parallel Tempering in R with Rmpi

October 6, 2013 | Lindons Log » R

My office computer recently got a really nice upgrade and now I have 8 cores on my desktop to play with. I also at the same time received some code for a Gibbs sampler written in R from my adviser. I wanted to try a metropolis-coupled markov chain monte carlo, , algorithm ... [Read more...]

Sixth Torino R net meeting and free Sweave Course

October 6, 2013 | TorinoR.net

On 21 November 2013 – 14:00 there will be a free Sweave course and starting at 16:30 there will be the Sixth Torino R net meeting. Events will take place at Campus Luigi Einaudi, Università degli Studi di Torino. Please visit events‘ page for details and if … Continue reading → [Read more...]

Post 2: Generating fake data

October 6, 2013 | Nathan VanHoudnos

In order to check that an estimation algorithm is working properly, it is useful to see if the algorithm can recover the true parameter values in one or more simulated "test" data sets. This post explains how to build such … Continue reading → [Read more...]

Topic Modeling in R

October 6, 2013 | suresh kumar Gorakala

As a part of Twitter Data Analysis, So far I have completed Movie review using R & Document Classification using R. Today we will be dealing with discovering topics in Tweets, i.e. to mine the tweets data to discover underlying topics– approach known as Topic Modeling.What is Topic Modeling?... [Read more...]

Influence Analysis for Repeated Measures Data

October 6, 2013 | Wingfeet

I am trying exercise 59.8 (page 5057) of the SAS/STAT Users Guide 12.3 in R. The interesting thing is that influence is investigated on subject level rather than individual level. The diagnostics in nlme does not do leave-subject-out, at least, not tha... [Read more...]

Simplicity Explained by The Author

October 4, 2013 | klr

Source is usually best explained by the source.  Ramnath Vaidyanathan provides an excellent look under the hood in his tutorial on rCharts explaining how he integrates the new d3 library uvCharts. If you want to explore further, here is a list of... [Read more...]

Financial Data Accessible from R

October 4, 2013 | rtraderadmin

This post lists the sources and types of financial data that is accessible directly from R. I included here free and non free ressources. Obviously given the size and the activity of the R community this is work in constant progress. I might update thi... [Read more...]

Post 1: A Bayesian 2PL IRT model

October 4, 2013 | Nathan VanHoudnos

In this post, we define the Two-Parameter Logistic (2PL) IRT model, derive the complete conditionals that will form the basis of the sampler, and discuss our choice of prior specification. We can find the appropriate values of numerically in R … Continue reading → [Read more...]

Post 0: Getting Started with R

October 4, 2013 | Nathan VanHoudnos

R is an interpreted programming language that makes it easy to think about statistics instead of thinking about programming. Unlike other programming languages, R is commonly used by typing commands one-at-a-time in an interactive session. RStudio is a program that … Continue reading → [Read more...]

Questions on my online forecasting course

October 3, 2013 | Rob J Hyndman

I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers. Do I need to use the Revolution Enterprise version of R, or can I use open-source R? Open source R is fine. Revolution Analytics is organizing the course, but there is ... [Read more...]
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