# 329 search results for "evaluation"

## R for Quants, Part III (A)

February 18, 2012
By

This is the third part in a three part series on teaching R to MFE students at CUNY Baruch. The …Continue reading »

## R for Quants, Part I (B)

February 13, 2012
By

This is a continuation of the R workshop I’m teaching at the Baruch MFE program. This section discusses the programming …Continue reading »

## Sorting in R as Inefficiently as Possible

January 12, 2012
By
$Sorting in R as Inefficiently as Possible$

My last post of substance was all about improving your performance using R to answer programming questions that might be asked during a job interview.  So let's say you nailed the interview and got the job, but you desperately want to be fired for grand incompetence.  Never fear, your pal at librestats once again has your back. The sleep...

## Introduction to Kaggle Algorithmic Trading Challenge

January 10, 2012
By

I recently participated in the Kaggle Algorithmic Trading Competition under the username VikP. For those who do not know what Kaggle is, it is a web site where individuals and corporations can host data analysis competitions. This particular competit...

## Introduction to Kaggle Algorithmic Trading Challenge

January 10, 2012
By

I recently participated in the Kaggle Algorithmic Trading Competition under the username VikP. For those who do not know what Kaggle is, it is a web site where individuals and corporations can host data analysis competitions. This particular competiti...

## Harmonic means, again again

January 9, 2012
By

Another arXiv posting I had had no time to comment is Nial Friel’s and Jason Wyse’s “Estimating the model evidence: a review“. This is a review in the spirit of two of our papers, “Importance sampling methods for Bayesian discrimination between embedded models” with Jean-Michel Marin (published in Jim Berger Feitschrift, Frontiers of Statistical Decision

## Working with data frames

January 5, 2012
By

R, just like other programming languages, has different types of objects. Matrices, arrays, data.frames, lists, vectors, tables, etc. But by far the most important for working with baseball data is going to be dataframes.I'm not sure of the level of ex...

## The ‘R’ in Human [R]esources (or: a very brief introduction to the statistical package ‘R’ for HR)

December 21, 2011
By

I studied psychology in Marburg (Germany). At university we exclusively used SPSS. The courses were among my classmates usually not the most popular. After over 10 years in management consulting, I have noticed that little has changed to this. It’s a shame because a lot of interesting data in consulting firms and HR departments remain unused. In my role as managing director of kibit GmbH, I have placed the focus of the company on ”R” … Weiterlesen →

## Ripley on model selection, and some links on exploratory model analysis

December 17, 2011
By

This is really fun. I love how Ripley thinks, with just about every concept considered in broad generality while being connected to real-data examples. He’s a great statistical storyteller as well. . . . and Wickham on exploratory model analysis I came across Ripley’s slides in a reference from Hadley Wickham’s article on exploratory model The post Ripley...