SAS PROC MCMC example 12 in R: Change point model

June 21, 2015
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SAS PROC MCMC example 12 in R: Change point model

I restarted at working my way through the PROC MCMC examples. The SAS manual describes this example: Consider the data set from Bacon and Watts (1971), where  is the logarithm of the height of the stagnant surface layer and the covariate...

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Statistics Be

June 20, 2015
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Statistics Be

This modern statistics got me confused, To tell you friends I’m quite unenthused. This modern statistics got me confused, To tell you friends I’m quite unenthused. I like Pee Wee Fisher or the great Jerzy But can’t make head nor tail of this Robby Tibsh’rani With his Oop-pop-a-da Be-a-ba-du-la-be-plee Ple-oobly-oobly-oobly-oobie Chum-cheeree-a-bah Oop-pop-a-dee-de-doom ah-ah! Robby Tibsh’rani […] The post Statistics Be appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Aarhus June 24-26 SoFiE

June 20, 2015
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The Aarhus June 24-26 2015 annual meeting of the Society for Financial Econometrics (SoFiE) is looking tremendous, thanks to the local organizers at  CREATES, Torben Andersen and his fine program committee, SoFiE staff, and the...

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Mathematics and Applied Statistics Lesson of the Day – Contrasts

Mathematics and Applied Statistics Lesson of the Day – Contrasts

A contrast is a linear combination of a set of variables such that the sum of the coefficients is equal to zero.  Notationally, consider a set of variables . Then the linear combination is a contrast if . There is a reason for why I chose to use as the symbol for the variables in […]

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Mathematics and Applied Statistics Lesson of the Day – Contrasts

Mathematics and Applied Statistics Lesson of the Day – Contrasts

A contrast is a linear combination of a set of variables such that the sum of the coefficients is equal to zero.  Notationally, consider a set of variables . Then the linear combination is a contrast if . There is a reason for why I chose to use as the symbol for the variables in […]

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In which a complete stranger offers me a bet

June 19, 2015
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In which a complete stranger offers me a bet

Piotr Mitros wrote to Deb and me: I read, with pleasure, your article about the impossibility of biasing a coin. I’m curious as to whether researchers believe what they write. Would you be willing to place some form of iterated bet? For example: I provide a two-sided coin and a table. The table looks like […] The post In which a complete stranger offers me a bet appeared first on…

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Can You change Your Bayesian prior? (ii)

June 18, 2015
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Can You change Your Bayesian prior? (ii)

This is one of the questions high on the “To Do” list I’ve been keeping for this blog.  The question grew out of discussions of “updating and downdating” in relation to papers by Stephen Senn (2011) and Andrew Gelman (2011) in Rationality, Markets, and Morals.[i] “As an exercise in mathematics [computing a posterior based on the client’s prior probabilities] […]

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Free Webinar: Intro to SparkR

June 18, 2015
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Are you interested in combining the power of R and Spark?  An “Intro to SparkR” webinar will take place on July 15, 2015 at 10 am California time. Everyone is welcome to attend. Agenda: – What is SparkR? – Recent … Continue reading →

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You can crush us, you can bruise us, yes, even shoot us, but oh—not a pie chart!

June 18, 2015
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You can crush us, you can bruise us, yes, even shoot us, but oh—not a pie chart!

Byron Gajewski pointed me to this several-years-old article from the Onion, which begins: According to a groundbreaking new study published Monday in The Journal Of The American Statistical Association, somewhere on the planet someone is totally doing it at this very moment. “Of the 6.7 billion inhabitants of Earth, approximately 3.5 billion have reached sexual […] The post You can crush us, you can bruise us, yes, even shoot us,…

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Big Data and Chess Follow-up: Predictive Piece Values Over the Course of a Game

June 17, 2015
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Big Data and Chess Follow-up: Predictive Piece Values Over the Course of a Game

In a previous post I used the the Million Base 2.2 chess data base to calculate the predictive piece values of chess pieces. It worked out pretty well and here, just for fun, I thought I would check out what happens with the predictive piece values o...

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dynamic mixtures [at NBBC15]

June 17, 2015
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dynamic mixtures [at NBBC15]

A funny coincidence: as I was sitting next to Arnoldo Frigessi at the NBBC15 conference, I came upon a new question on Cross Validated about a dynamic mixture model he had developed in 2002 with Olga Haug and Håvård Rue [whom I also saw last week in Valencià]. The dynamic mixture model they proposed replaces […]

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‘Variable Importance Plot’ and Variable Selection

June 17, 2015
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‘Variable Importance Plot’ and Variable Selection

Classification trees are nice. They provide an interesting alternative to a logistic regression.  I started to include them in my courses maybe 7 or 8 years ago. The question is nice (how to get an optimal partition), the algorithmic procedure is nice (the trick of splitting according to one variable, and only one, at each node, and then to move forward, never backward), and the visual output is just perfect (with that tree structure).…

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Link: Visualization Publication Data Collection

June 17, 2015
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People from Georgia Tech, INRIA, University of Stuttgart, and other institutions have put together a comprehensive dataset of all papers presented at Vis/VisWeek/VIS since 1990. This was first collected for a set of visualizations last year, but has been updated with the 2014 data. They intend on keeping it up to date.The dataset contains not just … Continue reading Link: Visualization Publication Data Collection

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Born-open data

June 17, 2015
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Born-open data

Jeff Rouder writes: Although many researchers agree that scientific data should be open to scrutiny to ferret out poor analyses and outright fraud, most raw data sets are not available on demand. There are many reasons researchers do not open their data, and one is technical. It is often time consuming to prepare and archive […] The post Born-open data appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Everything you wanted to know about writing SAS/IML modules

June 17, 2015
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Everything you wanted to know about writing SAS/IML modules

One of the fundamental principles of computer programming is to break a task into smaller subtasks and to modularize the program by encapsulating each subtask into its own function. I have written many blog posts over the years about how to define and use functions in the SAS/IML language. I […] The post Everything you wanted to know about writing SAS/IML modules appeared first on The DO Loop.

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Stan workshops at UCLA (6/23) and UCI (6/24)

June 17, 2015
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Stan workshops at UCLA (6/23) and UCI (6/24)

While Bob travels to Boston-ish, I’ll be giving two Stan workshops in Southern California. I’m excited to be back on the west coast for a few days — I grew up not too far away. Both workshops are open, but space is limited. Follow the links for registration. UCLA Social Statistics Seminar Series, 6/23, 10 […] The post Stan workshops at UCLA (6/23) and UCI (6/24) appeared first on Statistical…

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Interview at Leanpub

June 17, 2015
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A few weeks ago I sat down with Len Epp over at Leanpub to talk about my recently published book R Programming for Data Science. So far, I've only published one book through Leanpub but I'm a huge fan. They've developed a system that is, in my opinion, perfect for academic publishing. The book's written

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The David Brooks files: How many uncorrected mistakes does it take to be discredited?

June 16, 2015
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The David Brooks files:  How many uncorrected mistakes does it take to be discredited?

OK, why am I writing this? We all know that New York Times columnist David Brooks deals in false statistics, he’s willing and able to get factual matters wrong, he doesn’t even fact-check his own reporting, his response when people point out his mistakes is irritation rather than thanks, he won’t run a correction even […] The post The David Brooks files: How many uncorrected mistakes does it take to…

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Michael LaCour in 20 years

June 16, 2015
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Michael LaCour in 20 years

In case you were wondering what “Bruno” Lacour will be doing a couple decades from now . . . James Delaney pointed me to this CNN news article, “Connecticut’s strict gun law linked to large homicide drop” by Carina Storrs: The rate of gun-related murders fell sharply in the 10 years after Connecticut implemented a […] The post Michael LaCour in 20 years appeared first on Statistical Modeling, Causal Inference,…

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The Day After the Half Day in the Life of a Data Scientist

June 16, 2015
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In the last installment, I embarked on a project--perhaps only a task--to assemble a membership list for an organization. It sounded simple: how hard could it be to merge two lists of people? Of course, I couldn’t just stitch one list on top of the other as there are members who subscribed to the newsletter as well as joined the Facebook group. These duplicate rows must be merged so that…

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How to place titles in lattice plots

June 16, 2015
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How to place titles in lattice plots

I like the Economist theme in the latticeExtra package. It produces nice looking charts that mimic the design of the weekly newspaper, such as in this example:For some time I wondered how I could put the title of my lattice plots into the top left corn...

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North American seminars: June 2015

June 16, 2015
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North American seminars: June 2015

For the next few weeks I am travelling in North America and will be giving the following talks. 19 June: Southern California Edison, Rosemead CA. “Probabilistic forecasting of peak electricity demand”. 23 June: International Symposium on Forecasting, Riverside CA. “MEFM: An R package for long-term probabilistic forecasting of electricity demand”. 25 June: Google, Mountain View, CA. “Automatic algorithms […]

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How tall is Kit Harrington? Stan wants to know.

June 16, 2015
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How tall is Kit Harrington?  Stan wants to know.

We interrupt our regularly scheduled programming for a special announcement. Madeleine Davies writes: “Here are some photos of Kit Harington. Do you know how tall he is?” I’m reminded, of course, of our discussion of the height of professional tall person Jon Lee Anderson: Full Bayes, please. I can’t promise publication on Gawker, but I’ll […] The post How tall is Kit Harrington? Stan wants to know. appeared first on…

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