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.

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.

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-monte-carlo-simulation-confidence-intervals-for-nls-models/, but here we will take a different approach: First- and second-order

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 is by far the most commonly … Continue reading...

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 ...

After more than 3 years of development, we release the first official version of the OpenCPU system. Based on feedback and experiences from the beta series, OpenCPU version 1.0 has been rewritten entirely from scratch. The result is simple and flexible API that is easier to understand yet more powerful than before. With the new release also comes a new website and...

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...

I’m jumping around analytics environments these days and have to leave the comfort of my Mac’s RStudio Desktop application to use various RStudio Server instances via browser. While I prefer to use Chrome, the need to have a “dedicated” RStudio Server client outweighs the utility of my favorite browser. This is where Fluid (@FluidApp by

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 seconds) and extending RSiteCatalyst Version 1.1...