# 337 search results for "evaluation"

## Model fitting exam problem

May 20, 2013
By

Recently I have run an exam where the following question had risen many problems for students (here I give its shortened formulation). You are given the data generating process y = 10x + e, where e is error term. Fit linear regression using lm, ne...

## awalé

May 12, 2013
By

Following Le Monde puzzle #810, I tried to code an R program (not reproduced here) to optimise an awalé game but the recursion was too rich for R: even with a very small number of holes and seeds in the awalé… Searching on the internet, it seems the computer simulation of a winning strategy for

## Feature Selection 2 – Genetic Boogaloo

May 8, 2013
By

Previously, I talked about genetic algorithms (GA) for feature selection and illustrated the algorithm using a modified version of the GA R package and simulated data. The data were simulated with 200 non-informative predictors and 12 linear effects and three non-linear effects. Quadratic discriminant analysis (QDA) was used to model the data. The last set of...

## Feature Selection Strikes Back (Part 1)

April 29, 2013
By

In the feature selection chapter, we describe several search procedures ("wrappers") that can be used to optimize the number of predictors. Some techniques were described in more detail than others. Although we do describe genetic algorithms and how they can be used for reducing the dimensions of the data, this is the first of series of blog posts that...

## Poor man’s integration – a simulated visualization approach

April 29, 2013
By
$Poor man’s integration – a simulated visualization approach$

Every once in a while I encounter a problem that requires the use of calculus. This can be quite bothersome since my brain has refused over the years to retain any useful information related to calculus. Most of my formal training in the dark arts was completed in high school and has not been covered

## FasteR! HigheR! StrongeR! – A Guide to Speeding Up R Code for Busy People

April 25, 2013
By

This is an overview of tools for speeding up your R code that I wrote for the Davis R Users’ Group. First, Ask “Why?” It’s customary to quote Donald Knuth at this point, but instead I’ll quote my twitter buddy Ted Hart to illustrate a point: I’m just going to say it.I like for loops in #Rstats,...

## Time Varying Higher Moments with the racd package.

April 22, 2013
By

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have been able to answer.

## Time Varying Higher Moments with the racd package.

April 22, 2013
By

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have been able to answer.

## Mapping the GDELT data (and some Russian protests, too)

April 15, 2013
By

(This article was first published on Quantifying Memory, and kindly contributed to R-bloggers) In this post I show how to select relevant bits of the GDELT data in R and present some introductory ideas about how to visualise it as a network map. I've included all the code used to generate the illustrations. Because of this, if you here...