I discuss some advantages of Generalized Boosted Models over logistic regression and discriminant analysis and demonstrate how to use a GBM for binary classification (predicting whether an event occurs or not). Using a GBM for Classification in R from... [Read more...]

Local polynomial regression models can be used as a more flexible alternative to linear regression. However, the nonparametric regression models are slightly more difficult to estimate and interpret than linear regression. This video explains almost ev... [Read more...]

I provide an introduction to using logistic regression for prediction (binary classification) using the Titanic data competition from www.Kaggle.com as an example. I use models to predict in missing data, estimate a logistic regression model on a trai... [Read more...]

For more R resources, check out R-Bloggers! I seriously learn something every day from this site. [Read more...]

As mentioned in a previous post, Alex Hanna and I had the opportunity to teach last week at the Higher School of Economic’s International Social Network Analysis Summer School in St. Petersburg.  While last year’s workshop emphasized smaller social networks, this year’s workshop focused on online networks.  ... [Read more...]

The Ornstein-Uhlenbeck process is mean reverting process commonly used to model commodity prices. I demonstrate how to estimate the process using a set of price data and provide a function for simulation. [Read more...]

I’ve written a few previous posts comparing R to Python in terms of symbolic math, optimization, and bootstrapping. All of these posts were pretty popular. The last one especially. Many of the commenters brought up the fact that R, while … Continue reading → [Read more...]

Initial Remark: Reload this page if formulas don’t display well! As promised, here is the second part on how to obtain confidence intervals for fitted values obtained from nonlinear regression via nls or nlsLM (package ‘minpack.lm’). I covered a Monte Carlo approach in http://rmazing.wordpress.com/2013/08/14/predictnls-part-1... [Read more...]

How does Value at Risk change through time for the same portfolio? Previously There has been a number of posts on Value at Risk, including a basic introduction to Value at Risk and Expected Shortfall. The components garch model was also described. Issue The historical method for Value at Risk ... [Read more...]

This is a short tutorial on knitr/markdown and JS visualization packages googleVis and rCharts. With these packages you can create web pages with interactive visualizations just using R. This will require minimal or no knowledge of HTML ... [Read more...]

the national longitudinal survey of adolescent health (addhealth) is to the health and retirement study what teen people is to aarp magazine.  both surveys have followed a cohort of respondents for almost twenty years now, asking them health behav... [Read more...]

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This is your fast track to enterprise performance analysis and capacity planning with an emphasis on applying R statistical tools to your performance data. Early-bird discounts are available for the Level III Guerrilla Data Analysis Techniques class O... [Read more...]

RSiteCatalyst version 1.1 is now available on CRAN. Changes from version 1 include: Support for Correlations/Subrelations in the QueueRanked function Support for Current Data in all ‘Queue‘ functions Support Anomaly Detection for QueueOvertime and QueueTrended functions (example usage with ggplot2 graph) Decrease in wait time for API calls (from 5 seconds to 2 ... [Read more...]

Here is the link to the article: http://rpubs.com/hughes/7812 There you will discover how to simulate and fit: power function, Michaelis-Menten equation and sigmoid curves in R, the fit is done by least-square using the ‘nls’ function.Filed under: R and Stat Tagged: NLS, R [Read more...]

Last week I tried exercise 1 of the SAS(R) proc mixed with R libraries lme4 and MCMCglm. So this week I aimed for exercise 2 but ended up redoing exercise 1 with nlme.Exercise 2 results gave me problems with library lme4 and latter parts of the ex... [Read more...]

Hey, To illustrate generally complex probability density functions on continuous spaces, researchers always use the same examples, for instance mixtures of Gaussian distributions or a banana shaped distribution defined on with density function: If we draw a sample from this distribution using MCMC we obtain a [scatter]plot like this ... [Read more...]

Writing code from scratch to do parallel computations can be rather tricky. However, the packages providing parallel facilities in R make it remarkably easy. One such package is foreach. I am going to document my trail of discovery with foreach, which began some time ago, but has really come into ... [Read more...]

Recently I was looking to buy a used car. I was using the Edmunds website to estimate the true market value of a used car. It has a nice click through interface where it guides you to input make, model, … Continue reading → [Read more...]

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