Prediction intervals too narrow

October 22, 2014
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Prediction intervals too narrow

Almost all prediction intervals from time series models are too narrow. This is a well-known phenomenon and arises because they do not account for all sources of uncertainty. In my 2002 IJF paper, we measured the size of the problem by computing the actual coverage percentage of the prediction intervals on hold-out samples. We found […]

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Example 2014.12: Changing repeated measures data from wide to narrow format

October 21, 2014
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Example 2014.12: Changing repeated measures data from wide to narrow format

Data with repeated measures often come to us in the "wide" format, as shown below for the HELP data set we use in our book. Here we show just an ID, the CESD depression measure from four follow-up assessments, plus the baseline CESD. Obs ID CESD...

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Modeling Plenitude and Speciation by Jointly Segmenting Consumers and their Preferences

October 21, 2014
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Modeling Plenitude and Speciation by Jointly Segmenting Consumers and their Preferences

In 1993, when music was sold in retail stores, it may have been informative to ask about preference across a handful of music genre. Today, now that the consumer has seized control and the music industry has responded, the market has exploded into more...

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Statistics with a Feeling of Joy

October 21, 2014
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Statistics with a Feeling of Joy

‘Attacking statistical problems with a feeling of joy.. and not from a position of fear and self-doubt’. That’s the message …Continue reading →

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Try a spaghetti plot

October 21, 2014
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Try a spaghetti plot

Joe Simmons writes: I asked MTurk NFL fans to consider an NFL game in which the favorite was expected to beat the underdog by 7 points in a full-length game. I elicited their beliefs about sample size in a few different ways (materials .pdf; data .xls). Some were asked to give the probability that the better […] The post Try a spaghetti plot appeared first on Statistical Modeling, Causal Inference, and…

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Rant: Academic "Letterhead" Requirements

October 21, 2014
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(All rants, including this one, are here.)Countless times, from me to Chair/Dean xxx at Some Other University: I am happy to help with your evaluation of Professor zzz. This email will serve as my letter. [email here]...Countless times, from&...

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Approximating the impact of inflation

October 21, 2014
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Approximating the impact of inflation

The other day someone mentioned to me a rule of thumb he was using to estimate the number of years \(n\) it would take for inflation to destroy half of the purchasing power of today's money: \[ n = \frac{70}{p}\] Here \(p\) is the inflation in percent,...

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Degrees of Choice: A modification of a WSJ graphic

October 20, 2014
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This post uses ggplot2 and rCharts to modify a grouped bar chart that appeared in an article that appeared online on October 19, 2014 in Wall Street Journal’s site. The article was titled “How to Sell a Liberal-Arts Education”. The code for ...

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Thinking like a statistician: don’t judge a society by its internet comments

October 20, 2014
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Thinking like a statistician: don’t judge a society by its internet comments

In a previous post I explained how thinking like a statistician can help you avoid  feeling sad after using Facebook. The basic point was that missing not at random (MNAR) data on your friends' profiles (showing only the best parts of their life) can result in the biased view that your life is boring and uninspiring in

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Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman

October 20, 2014
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Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman

Big data is all the rage, but sometimes you don’t have big data. Sometimes you don’t even have average size data. Sometimes you only have eleven unique socks: Karl Broman is here putting forward a very interesting problem. Interesting, not onl...

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Three ways to present a probability forecast, and I only like one of them

October 20, 2014
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Three ways to present a probability forecast, and I only like one of them

To the nearest 10%: To the nearest 1%: To the nearest 0.1%: I think the National Weather Service knows what they’re doing on this one. The post Three ways to present a probability forecast, and I only like one of them appeared first on Statist...

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On deck this week

October 20, 2014
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Mon: Three ways to present a probability forecast, and I only like one of them Tues: Try a spaghetti plot Wed: I ain’t got no watch and you keep asking me what time it is Thurs: Some questions from our Ph.D. statistics qualifying exam Fri: Solution to the helicopter design problem Sat: Solution to the […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…

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Compute the log-determinant of an arbitrary matrix

October 20, 2014
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Compute the log-determinant of an arbitrary matrix

A few years ago I wrote an article that shows how to compute the log-determinant of a covariance matrix in SAS. This computation is often required to evaluate a log-likelihood function. My algorithm used the ROOT function in SAS/IML to compute a Cholesky decomposition of the covariance matrix. The Cholesky […]

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Compute the log-determinant of an arbitrary matrix

October 20, 2014
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Compute the log-determinant of an arbitrary matrix

A few years ago I wrote an article that shows how to compute the log-determinant of a covariance matrix in SAS. This computation is often required to evaluate a log-likelihood function. My algorithm used the ROOT function in SAS/IML to compute a Cholesky decomposition of the covariance matrix. The Cholesky […]

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hts with regressors

October 20, 2014
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hts with regressors

The hts package for R allows for forecasting hierarchical and grouped time series data. The idea is to generate forecasts for all series at all levels of aggregation without imposing the aggregation constraints, and then to reconcile the forecasts so they satisfy the aggregation constraints. (An introduction to reconciling hierarchical and grouped time series is […]

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The VIS Sports Authority

October 19, 2014
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The VIS Sports Authority

When you think of a conference, does sitting around a lot come to mind? Lots of food? Bad coffee? No time to work out? For the first time in VIS history, there will be a way to exercise your body, not just your mind. The VIS Sports Authority, which is totally an official thing that I didn’t just make up, will kick your ass at VIS 2014.

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“Your Paper Makes SSRN Top Ten List”

October 19, 2014
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I received the following email from the Social Science Research Network, which is a (legitimate) preprint server for research papers: Dear Andrew Gelman: Your paper, “WHY HIGH-ORDER POLYNOMIALS SHOULD NOT BE USED IN REGRESSION DISCONTINUITY DESIGNS”, was recently listed on SSRN’s Top Ten download list for: PSN: Econometrics, Polimetrics, & Statistics (Topic) and Political Methods: […] The post “Your Paper Makes SSRN Top Ten List” appeared first on Statistical Modeling,…

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Tuning Laplaces Demon II

October 19, 2014
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Tuning Laplaces Demon II

I am continuing with my trying all algorithms of Laplaces Demon. It is actually quite a bit more work than I expected but I do find that some of the things get clearer. Now that I am close to the end of calculating this second batch I learned that ther...

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PhilStat/Law: Nathan Schachtman: Acknowledging Multiple Comparisons in Statistical Analysis: Courts Can and Must

October 19, 2014
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PhilStat/Law: Nathan Schachtman: Acknowledging Multiple Comparisons in Statistical Analysis: Courts Can and Must

The following is from Nathan Schachtman’s legal blog, with various comments and added emphases (by me, in this color). He will try to reply to comments/queries. “Courts Can and Must Acknowledge Multiple Comparisons in Statistical Analyses” Nathan Schachtman, Esq., PC * October 14th, 2014 In excluding the proffered testimony of Dr. Anick Bérard, a Canadian perinatal […]

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Hoe noem je?

October 18, 2014
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Haynes Goddard writes: Reviewing my notes and books on categorical data analysis, the term “nominal” is widely employed to refer to variables without any natural ordering. I was a language major in UG school and knew that the etymology of nominal is the Latin word nomen (from the Online Etymological Dictionary: early 15c., “pertaining to […] The post Hoe noem je? appeared first on Statistical Modeling, Causal Inference, and Social…

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Econometric Research Resources

October 17, 2014
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Econometric Research Resources

The following page, put together by John Kane at the Department of Economics, SUNY-Oswego, has some very useful links for econometrics students and researchers: Econometric Research Resources. © 2014, David E. Giles

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Bayes Rule in an animated gif

October 17, 2014
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Bayes Rule in an animated gif

Say Pr(A)=5% is the prevalence of a disease (% of red dots on top fig). Each individual is given a test with accuracy Pr(B|A)=Pr(no B| no A) = 90% .  The O in the middle turns into an X when the test fails. The rate of Xs is 1-Pr(B|A). We want to know the probability

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How do companies use Bayesian methods?

October 17, 2014
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Jason May writes: I’m in Northwestern’s Predictive Analytics grad program. I’m working on a project providing Case Studies of how companies use certain analytic processes and want to use Bayesian Analysis as my focus. The problem: I can find tons of work on how one might apply Bayesian Statistics to different industries but very little […] The post How do companies use Bayesian methods? appeared first on Statistical Modeling, Causal…

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