Converting plots to data II

January 26, 2014
By
Converting plots to data II

There were quite some reactions on lasts week's post converting plots to data. Two additional programs were mentioned; WebPlotDigitzier and DataThief. Note that google or wikipedia has a bunch of alternatives. Datathief is shareware, a java program, so...

Read more »

Alexander Aitken

January 26, 2014
By
Alexander Aitken

Alexander Aitken was one of New Zealand's greatest mathematicians - see my earlier post. As an econometrician, you may be very surprised how much you owe him!Want to check out more about this amazing man? See www.nzedge.com/alexander-aitken/ .© 2014, ...

Read more »

Introduction to the particle Gibbs sampler

January 25, 2014
By
Introduction to the particle Gibbs sampler

Introduction Particle MCMC (the use of approximate SMC proposals within exact MCMC algorithms) is arguably one of the most important developments in computational Bayesian inference of the 21st Century. The key concepts underlying these methods are described in a famously impenetrable “read paper” by Andrieu et al (2010). Probably the most generally useful method outlined […]

Read more »

Introduction to the particle Gibbs sampler

January 25, 2014
By
Introduction to the particle Gibbs sampler

Introduction Particle MCMC (the use of approximate SMC proposals within exact MCMC algorithms) is arguably one of the most important developments in computational Bayesian inference of the 21st Century. The key concepts underlying these methods are described in a famously impenetrable “read paper” by Andrieu et al (2010). Probably the most generally useful method outlined […]

Read more »

Big Data Events

January 25, 2014
By
Big Data Events

The Big Data discussion builds momentum in Official Statistics. In October 2012 at the UNECE High-level Seminar on Modernization of Statistical …Continue reading →

Read more »

Big Data Events

January 25, 2014
By
Big Data Events

The Big Data discussion builds momentum in Official Statistics. In October 2012 at the UNECE High-level Seminar on Modernization of Statistical …Continue reading →

Read more »

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

January 25, 2014
By

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 ›

Read more »

Xihong Lin on sparsity and density

January 25, 2014
By

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,…

Read more »

Overnight vs. Intraday ETF Returns

January 25, 2014
By

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 […]

Read more »

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 […]

Read more »

Testing Up, or Testing Down?

January 24, 2014
By
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...

Read more »

Advice to a Prospective Biostatistician

January 24, 2014
By

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...

Read more »

CO2 Emissions per Dollar

January 24, 2014
By
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…

Read more »

Rob Hyndman on Forecasting

January 24, 2014
By
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...

Read more »

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

January 24, 2014
By
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...

Read more »

Parables vs. stories

January 24, 2014
By
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.

Read more »

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 […]

Read more »

Peer Review, Part 5: The Importance of Gatekeepers

January 24, 2014
By
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 […]

Read more »

Thoughts on the Ljung-Box test

January 24, 2014
By
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…

Read more »

Precision, with Imprecise Words

January 24, 2014
By
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…

Read more »

An ARDL Add-in for EViews

January 24, 2014
By
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...

Read more »

Jim Hamilton on R-Squared and Economic Prediction

January 23, 2014
By
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...

Read more »

Bayesian statistics in Montreal

January 23, 2014
By
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...

Read more »


Subscribe

Email:

  Subscribe