I was drawn to this Wall Street Journal chart because of the blue columns. The blue color solves a common problem in time-series plots when the time axis is incomplete. The first quarter of 2015 is dangling. The article is...

I'm baaaaaack...Speaking of being back, I'm just back from the Rob Engle / NYU Volatility Institute Annual Conference. (Well, more or less just back.) Great people, great science, tightly-focused on a fascinating and timely area, the bond market ...

Another occurrence [out of many!] of a question on X validated where the originator (primitivus petitor) was trying to get an explanation without the proper background. On either Bayesian statistics or simulation. The introductory sentence to the question was about “trying to understand how the choice of priors affects a Bayesian model estimated using MCMC” […]

Roger and I responded to the controversy around the journal that banned p-values today in Nature. A piece like this requires a lot of information packed into very little space but I thought one idea that deserved to be talked about more was the idea of data analysis subcultures. From the paper: Data analysis is taught

Wayne Lytle created this video about the Viz-O-Matic that provides lots of tools to make visualization glitzier. It’s a nice little spoof, and a throwback to the computer graphics of the early 1990s (it was made for SIGGRAPH 1993). This video was brought up in a discussion about storytelling at CHI last week, though I … Continue reading Video: The Danger of Glitziness

I wrote the following for the occasion of his recent retirement party but I thought these thoughts might of general interest: When Carl Morris came to our department in 1989, I and my fellow students were so excited. We all took his class. The funny thing is, though, the late 1980s might well have been […] The post Carl Morris: Man Out of Time [reflections on empirical Bayes] appeared first…

Suppose that you compute the correlation matrix (call it R1) for a set of variables x1, x2, ..., x8. For some reason, you later want to compute the correlation matrix for the variables in a different order, maybe x2, x1, x7,..., x6. Do you need to go back to the […] The post Create and use a permutation matrix in SAS appeared first on The DO Loop.

The BEST programs, for Bayesian estimation of two groups, were written with generic vague priors only minimally informed by the scale of the data. Here are new versions of the programs that are better suited for specifying informed priors.A little back...

As I wrote a couple years ago: Statistics does not require randomness. The three essential elements of statistics are measurement, comparison, and variation. Randomness is one way to supply variation, and it’s one way to model variation, but it’s not necessary. Nor is it necessary to have “true” randomness (of the dice-throwing or urn-sampling variety) […] The post What’s the most important thing in statistics that’s not in the textbooks?…

MONTHLY MEMORY LANE: 3 years ago: March 2012. I mark in red three posts that seem most apt for general background on key issues in this blog* (Posts that are part of a “unit” or a group of “U-Phils” count as one.) This new feature, appearing the last week of each month, began at the blog’s 3-year anniversary in Sept, 2014. *excluding those recently reblogged. April […]

A few days ago, I was asked if we should spend a lot of time to choose the distribution we use, in GLMs, for (actuarial) ratemaking. On that topic, I usually claim that the family is not the most important parameter in the regression model. Consider the following dataset > db <- data.frame(x=c(1,2,3,4,5),y=c(1,2,4,2,6)) > plot(db,xlim=c(0,6),ylim=c(-1,8),pch=19) To visualize a regression model, use the following code > nd=data.frame(x=seq(0,6,by=.1)) > add_predict = function(reg){…

I just read this charming article by Lee Wilkinson’s brother on a mathematician named Yitang Zhang. Zhang recently gained some fame after recently proving a difficult theorem, and he seems to be a quite unusual, but likable, guy. What I liked about Wilkinson’s article is how it captured Zhang’s eccentricities with affection but without condescension. […] The post Eccentric mathematician appeared first on Statistical Modeling, Causal Inference, and Social Science.

Mon: Eccentric mathematician Tues: What’s the most important thing in statistics that’s not in the textbooks? Wed: Carl Morris: Man Out of Time [reflections on empirical Bayes] Thurs: “The general problem I have with noninformatively-derived Bayesian probabilities is that they tend to be too strong.” Fri: Good, mediocre, and bad p-values Sat: Which of these […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…