Learning to use a data analysis tool well takes significant effort, so people tend to continue using the tool they learned in college for much of their careers. As a result, the software used by professors and their students is … Continue reading →

Being freshly elected ASA Fellow (yay!), I just received the list of 2012 ASA Fellows. Among whose, let me mention Sudipto Banerjee, University of Minnesota, Minneapolis, Minnesota, elected “For theoretical, methodological and applied research in spatiotemporal statistical modeling, especially as applied to problems in environmetrics, ecology, occupational health, agriculture and economics, for professional work at

Accounting for temporal dependence in econometric analysis is important, as the presence of temporal dependence violates the assumption that observations are independent units. Historically, much less attention has been paid to correcting for spatial dependence, which, if present, also violates this independence assumption. The comparability of temporal and spatial dependence is useful for illustrating why

How can we represent conversations between a small sample of users, such as the email or SMS converstations between James Murdoch’s political lobbiest and a Government minister’s special adviser (Leveson inquiry evidence), or the pattern of retweet activity around a couple of heavily retweeted individuals using a particular hashtag? I spent a bit of time

At this Monday’s Montreal R User Group meeting, Arthur Charpentier gave an interesting talk on the subject of quantile regression. One of the main messages I took away from the workshop was that quantile regression can be used to determine if extreme events are becoming more extreme. The example given was hurricane intensity since 1978.

The common approach to estimating a binary dependent variable regression model is to use either the logit or probit model. Both are forms of generalized linear models (GLMs), which can be seen as modified linear regressions that allow the dependent variable to originate from non-normal distributions. The coefficients in a linear regression model are marginal

I came across a free source of Intraday Forex data while reading Forex Trading with R : Part 1 post. You can download either Daily or Hourly historical Forex data from the FXHISTORICALDATA.COM. The outline of this post: Download and Import Forex data Reference and Plot Intraday data Daily Backtest Intraday Backtest First,I created a