Vectorisation is your best friend: replacing many elements in a character vector

January 25, 2014
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As with any programming language, R allows you to tackle the same problem in many different ways or styles. These styles differ both in the amount of code, readability, and speed. In this post I want to illustrate this by… See more ›

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Xihong Lin on sparsity and density

January 25, 2014
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I pointed Xihong Lin to this post from last month regarding Hastie and Tibshirani’s “bet on sparsity principle.” I argued that, in the worlds in which I work, in social and environmental science, every contrast is meaningful, even if not all of them can be distinguished from noise given a particular dataset. That is, I […]The post Xihong Lin on sparsity and density appeared first on Statistical Modeling, Causal Inference,…

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Overnight vs. Intraday ETF Returns

January 25, 2014
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I haven’t done much “googling” before posting, so this topic might have been covered elsewhere but I think it’s  really worth sharing or repeating anyway. A lot has been written about the source of  ETF returns (some insights might be found here). In a nutshell some analysis found that the bulk of the return is made […]

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Machine Learning Lesson of the Day – The “No Free Lunch” Theorem

Machine Learning Lesson of the Day – The “No Free Lunch” Theorem

A model is a simplified representation of reality, and the simplifications are made to discard unnecessary detail and allow us to focus on the aspect of reality that we want to understand.  These simplifications are grounded on assumptions; these assumptions may hold in some situations, but may not hold in other situations.  This implies that […]

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Testing Up, or Testing Down?

January 24, 2014
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Testing Up, or Testing Down?

Students are told that if you're going to go in for sequential testing, when determining the specification of a model, then the sequence that you follow should be "from the general to the specific". That is, you should start off with a "large" model, a...

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Advice to a Prospective Biostatistician

January 24, 2014
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This is advice to a prospective student wondering whether to go into public health/epi or biostatistics. I'm willing to blindly argue for biostatistics, but prospective students might find it more useful if I frame the issues so they can decide for the...

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CO2 Emissions per Dollar

January 24, 2014
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CO2 Emissions per Dollar

Originally posted on CoolStatsBlog:For all the flak China receives about its greenhouse gas emissions, the average Chinese produces less than a third the amount of CO2 than his American counterpart. It just so happens that there are 1.3 billion Chinese, and 0.3 billion Americans, so China ends up producing more CO2. Carbon dioxide and…

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Rob Hyndman on Forecasting

January 24, 2014
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Rob Hyndman on Forecasting

If you have an interest in forecasting, especially economic forecasting, the Rob Hyndman's name will be familiar to you. Hailing from my old stamping ground - Monash University - Rob is one of the world's top forecasting experts. Without going int...

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Phil 6334: Slides from Day #1: Four Waves in Philosophy of Statistics

January 24, 2014
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Phil 6334: Slides from Day #1: Four Waves in Philosophy of Statistics

First installment 6334 syllabus (Mayo and Spanos) D. Mayo slides from Day #1: Jan 23, 2014   I will post seminar slides here (they will generally be ragtag affairs), links to the papers are in the syllabus.Filed under: Phil 6334 class material, Phi...

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Parables vs. stories

January 24, 2014
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Parables vs. stories

God is in every leaf of every tree, but he is not in every leaf of every parable. Let me explain with a story. A few months ago I read the new book, Doing Data Science, by Rachel Schutt and Cathy O’Neal, and I came across the following motivation for comprehensive integration of data sources, […]The post Parables vs. stories appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Statistics and Chemistry Lesson of the Day – Illustrating Basic Concepts in Experimental Design with the Synthesis of Ammonia

Statistics and Chemistry Lesson of the Day – Illustrating Basic Concepts in Experimental Design with the Synthesis of Ammonia

To summarize what we have learned about experimental design in the past few Applied Statistics Lessons of the Day, let’s use an example from physical chemistry to illustrate these basic principles. Ammonia (NH3) is widely used as a fertilizer in industry.  It is commonly synthesized by the Haber process, which involves a reaction between hydrogen […]

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Peer Review, Part 5: The Importance of Gatekeepers

January 24, 2014
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Peer Review, Part 5: The Importance of Gatekeepers

The purpose of peer review is to separate the wheat from the chaff, the good from the bad, the brilliant from the clinically insane – you get the picture. But why? Why filter and not just let anybody publish whatever they want? Why Gatekeepers? And Why Gates? In the old days, there was the resource […]

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Thoughts on the Ljung-Box test

January 24, 2014
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Thoughts on the Ljung-Box test

It is common to use a Ljung-Box test to check that the residuals from a time series model resemble white noise. However, there is very little practical advice around about how to choose the number of lags for the test. The Ljung-Box test was proposed by Ljung and Box (Biometrika, 1978) and is based on the statistic     where is the length of the time series, is the th…

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Precision, with Imprecise Words

January 24, 2014
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Precision, with Imprecise Words

This morning, after my course on extreme values, some students did show me a question they got from practicals they were suppose to work on, with undergraduate students : To be more specific, they wanted some feedback about point B. Now, let’s make it clear : I have no idea what “precision” and “variation” could mean… But let’s try and see if we can get something usefull, that might help…

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An ARDL Add-in for EViews

January 24, 2014
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An ARDL Add-in for EViews

My posts on ARDL models and bounds testing (here and here) have certainly been popular. So, I was really pleased to see that Yashar Tarverdi has produced an "Add-In" for the EViews package that makes this type of econometric analysis somewhat easier.Yo...

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Jim Hamilton on R-Squared and Economic Prediction

January 23, 2014
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Jim Hamilton on R-Squared and Economic Prediction

I always tell my students that, when it comes to regression results, the value of the coefficient of determination (R2), is pretty much the last thing that I look at. And I'm serious! I've blogged about this before (see here, for example), but it's wor...

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Bayesian statistics in Montreal

January 23, 2014
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Bayesian statistics in Montreal

I am happy to announce that I will be offering my tutorial, "Bayesian Statistics Made Simple" at PyCon 2014 in Montreal.  The tutorial is based on material from Think Bayes.  It includes some of the examples and exercises in the book.  P...

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Summer courses and workshop in doing Bayesian data analysis

January 23, 2014
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Summer courses and workshop in doing Bayesian data analysis: Workshop, University of Oslo, Norway, June 4-6, 2014.Course offered through the University of St. Gallen Summer School in Empirical Research Methods (SSERM), St. Gallen, Switzerland, June 10-...

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Discussion on preregistration of research studies

January 23, 2014
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Discussion on preregistration of research studies

Chris Chambers and I had an enlightening discussion the other day at the blog of Rolf Zwaan, regarding the Garden of Forking Paths (go here and scroll down through the comments). Chris sent me the following note: I’m writing a book at the moment about reforming practices in psychological research (focusing on various bad practices […]The post Discussion on preregistration of research studies appeared first on Statistical Modeling, Causal Inference,…

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Rasmus Bååth’s Bayesian first aid

January 23, 2014
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Rasmus Bååth’s Bayesian first aid

Besides having coded a pretty cool MCMC app in Javascript, this guy Rasmus Bååth has started the Bayesian first aid project. The idea is that if there’s an R function called blabla.test performing test “blabla”, there should be a function bayes.blabla.test performing a similar test in a Bayesian framework, and showing the output in a […]

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Sampling with replacement: Now easier than ever in the SAS/IML language

January 23, 2014
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Sampling with replacement: Now easier than ever in the SAS/IML language

With each release of SAS/IML software, the language provides simple ways to carry out tasks that previously required more effort. In 2010 I blogged about a SAS/IML module that appeared in my book Statistical Programming with SAS/IML Software, which was written by using the SAS/IML 9.2. The blog post showed [...]

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Peer Review, Part 4: Good Reasons for Bad Papers

January 23, 2014
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Peer Review, Part 4: Good Reasons for Bad Papers

As a reviewer, you might sometimes ask yourself why people write so many bad papers. And why they bother submitting them. I certainly do. But where do they come from? Who submits bad papers? And why? It may come as a surprise, but there are good reasons to submit bad papers for review. To Get […]

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Slides from my online forecasting course

January 23, 2014
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Slides from my online forecasting course

Last year I taught an online course on forecasting using R. The slides and exercise sheets are now available at www.otexts.org/fpp/resources/

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