Convenient and innocuous priors

November 21, 2013
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Andrew Gelman has some interesting comments on non-informative priors this morning. Rather than thinking of the prior as a static thing, think of it as a way to prime the pump. … a non-informative prior is a placeholder: you can use the non-informative prior to get the analysis started, then if your posterior distribution is […]

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Future of Statistics take home messages. #futureofstats

November 21, 2013
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Future of Statistics take home messages. #futureofstats

A couple weeks ago we had the Future of Statistics Unconference. You can still watch it online here. Rafa also attended the Future of Statistical Sciences Workshop and wrote a great summary which you can read here. I decided to write … Continue reading →

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Hidden dangers of noninformative priors

November 21, 2013
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Following up on Christian’s post [link fixed] on the topic, I’d like to offer a few thoughts of my own. In BDA, we express the idea that a noninformative prior is a placeholder: you can use the noninformative prior to get the analysis started, then if your posterior distribution is less informative than you would […]The post Hidden dangers of noninformative priors appeared first on Statistical Modeling, Causal Inference, and…

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Using Database Joins to Compare Results Sets

November 20, 2013
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Using Database Joins to Compare Results Sets

One of the most powerful tools you can learn to use in genomics research is a relational database system, such as MySQL.  These systems are fairly easy to setup and use, and provide users the ability to organize and manipulate data and statistical...

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Erich Lehmann: Statistician and Poet

November 20, 2013
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Erich Lehmann: Statistician and Poet

Today is Erich Lehmann’s birthday. The last time I saw him was at the Second Lehmann conference in 2004, at which I organized a session on philosophical foundations of statistics (including David Freedman and D.R. Cox). I got to know Lehmann, Neyman’s first student, in 1997.  One day, I received a bulging, six-page, handwritten letter […]

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That’s crazy talk!

November 20, 2013
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Tenure track faculty opening at the Center for the Promotion of Research Involving Innovative Statistical Methodology, with Jennifer Hill, Marc Scott, and other world-class researchers. It looks like a great opportunity. The post That’s crazy ta...

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Light entertainment: Behold the 10 percent change!

November 20, 2013
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Light entertainment: Behold the 10 percent change!

Reader Orjan L. sent in this Swedish delight: It's on the last page of this report, and I'm told it's about the number of weapons seized by Swedish customs each year. *** On p. 8, I found a hockey-stick chart:...

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Write a reusable SAS/IML module that passes values to R

November 20, 2013
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Write a reusable SAS/IML module that passes values to R

When I call R from within the SAS/IML language, I often pass parameters from SAS into R. This feature enables me to write general-purpose, reusable, modules that can analyze data from many different data sets. I've previously blogged about how to pass values to SAS procedures from PROC IML by [...]

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NYT (non)-retraction watch

November 20, 2013
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Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! See here for two examples that particularly annoyed me, to the extent that I contacted various […]The post NYT (non)-retraction watch appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Raising Statistical Standards Effect on Sample Size

November 20, 2013
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The failure of mainstream research to consistently reproduce results have led many to look for the faults in current methodologies.One of these potential faults identified is that the significance levels of current standards is too high.  A standa...

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On the use of marginal posteriors in marginal likelihood estimation via importance-sampling

November 19, 2013
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On the use of marginal posteriors in marginal likelihood estimation via importance-sampling

Perrakis, Ntzoufras, and Tsionas just arXived a paper on marginal likelihood (evidence) approximation (with the above title). The idea behind the paper is to base importance sampling for the evidence on simulations from the product of the (block) marginal posterior distributions. Those simulations can be directly derived from an MCMC output by randomly permuting the […]

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Several things about education

November 19, 2013
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First, I saw Andrew Gelman's rant about "big bad education" (link) which leads me to Mark Palko's rant about teaching "the Law of Large Numbers" in the new "Common Core" curriculum for New York schools. Mark's conclusion being: If we start talking about setting aside significant time to cover probability and statistics accurately and in reasonable depth and put the ideas in proper context, you have my enthusiastic support, but…

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Practical Data Science with R: Manning Deal of the Day November 19th 2013

November 19, 2013
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Practical Data Science with R: Manning Deal of the Day November 19th 2013

Please share: Manning Deal of the Day November 19: Half off Practical Data Science with R. Use code dotd1119au at www.manning.com/zumel/. Related posts: Data Science, Machine Learning, and Statistics: what is in a name? Data science project planning S...

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A Survey Tool Designed Entirely in Shiny Surveying Users of R

November 19, 2013
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A Survey Tool Designed Entirely in Shiny Surveying Users of R

I have written a very basic survey tool built entirely in the Shiny package of R.  I hope the tool is useful.  Modifying the survey for your own purposes is trivially easy (I hope).I have not commented my code so it is pretty messy right now....

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More on “data science” and “statistics”

November 19, 2013
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After reading Rachel and Cathy’s book, I wrote that “Statistics is the least important part of data science . . . I think it would be fair to consider statistics as a subset of data science. . . . it’s not the most important part of data science, or even close.” But then I received […]The post More on “data science” and “statistics” appeared first on Statistical Modeling, Causal Inference,…

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A letter to high-school students

November 19, 2013
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Imagine Magazine, a youth-focused journal by Johns Hopkins's Center of Talented Youth, invited me to contribute an article in celebration of statistics. I try to convey the fun and joy of working with numbers and charts. You can read it...

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R and Solr Integration Using Solr’s REST APIs

November 19, 2013
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R and Solr Integration Using Solr’s REST APIs

Solr is the most popular, fast and reliable open source enterprise search platform from the Apache Luene project.  Among many other features, we love its powerful full-text search, hit highlighting, faceted search, and near real-time indexing. &nb...

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Predicting claims with a Bayesian network

November 19, 2013
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Predicting claims with a Bayesian network

Here is a little Bayesian Network to predict the claims for two different types of drivers over the next year, see also example 16.15 in [1]. Let's assume there are good and bad drivers. The probabilities that a good driver will have 0, 1 or 2 claims i...

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Lucien Le Cam: “The Bayesians hold the Magic”

November 18, 2013
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Lucien Le Cam: “The Bayesians hold the Magic”

Today is Lucien Le Cam’s birthday. He was an error statistician whose remarks in an article, “A Note on Metastatisics,” in a collection on foundations of statistics (Le Cam 1977)* had some influence on me.  A statistician at Berkeley, Le Cam was a co-editor with Neyman of the Berkeley Symposia volumes. I hadn’t mentioned him on […]

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Binomial regression model

November 18, 2013
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Binomial regression model

Most of the time, when we introduce binomial models, such as the logistic or probit models, we discuss only Bernoulli variables, . This year (actually also the year before), I discuss extensions to multinomial regressions, where  is a function on some simplex. The multinomial logistic model was mention here. The idea is to consider, for instance with three possible classes the following model and Now, what about a real Binomial model, , where ‘s are known. How…

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Feeling optimistic after the Future of the Statistical Sciences Workshop

November 18, 2013
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Last I week I participated in the Future of the Statistical Sciences Workshop. I arrived feeling somewhat pessimistic about the future of our discipline. My pessimism stemmed from the emergence of the term Data Science and the small role academic … Continue reading →

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Graduate Course on Copulas and Extreme Values

November 18, 2013
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This Winter, I will be giving a (graduate) course on extreme values, and copulas (more generally multivariate models and dependence), MAT8595. It is an ISM course, and even if it will probably be given in French, I will upload information here, in English. I will upload the (detailed) syllabus of the course during the Christmas holidays. But to give an overview, for those willing to register, the first part of the course will…

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What’s my Kasparov number?

November 18, 2013
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What’s my Kasparov number?

A colleague writes: Personally my Kasparov number is two: I beat ** in a regular tournament game, and ** beat Kasparov! That’s pretty impressive, especially given that I didn’t know this guy played chess at all! Anyway, this got me thinking, what’s my Kasparov number? OK, that’s easy. I beat Magnus Carlsen the other day […]The post What’s my Kasparov number? appeared first on Statistical Modeling, Causal Inference, and Social…

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