DNS/AFNS Yield Curve Modeling FAQ’s

January 15, 2014
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DNS/AFNS Yield Curve Modeling FAQ’s

It's hard to believe that I haven't yet said anything about yield-curve modeling and forecasting in the dynamic Nelson-Siegel (DNS) tradition, whether the original Diebold-Li (2006) DNS version or the Christensen-Diebold-Rudebusch (2011) arbitrage...

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Postdoc involving pathbreaking work in MRP, Stan, and the 2014 election!

January 15, 2014
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Postdoc involving pathbreaking work in MRP, Stan, and the 2014 election!

We’re working with polling company YouGov to track public opinion, state-by-state and district-by-district, during the 2014 campaign. We’ll be using multilevel regression and poststratification, and implementing it in Stan, and developing the necessary new parts of Stan to get this running scalably and efficiently. And we’ll be making the most detailed, up-to-date election forecasts. What […]The post Postdoc involving pathbreaking work in MRP, Stan, and the 2014 election! appeared first…

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Say hello to SAS Analytics 13.1

January 15, 2014
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Say hello to SAS Analytics 13.1

Late last month, while many of us were sipping eggnog and decking halls with boughs of holly, SAS released the 13.1 version of its analytical products. Readers of Maura Stokes' newsletter, SAS Statistics and Operations Research News (Nov 2013), have already been alerted to new features in products such as [...]

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Machine Learning Lesson of the Day – Parametric vs. Non-Parametric Models

Machine Learning Lesson of the Day – Parametric vs. Non-Parametric Models

A machine learning algorithm can be classified as either parametric or non-parametric. A parametric algorithm has a fixed number of parameters.  A parametric algorithm is computationally faster, but makes stronger assumptions about the data; the algorithm may work well if the assumptions turn out to be correct, but it may perform badly if the assumptions […]

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Example 2014.1: "Power" for a binomial probability, plus: News!

January 14, 2014
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Example 2014.1: "Power" for a binomial probability, plus: News!

Hello, folks! I'm pleased to report that Nick and I have turned in the manuscript for the second edition of SAS and R: Data Management, Statistical Analysis, and Graphics. It should be available this summer. New material includes some of our more po...

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Advice on writing research articles

January 14, 2014
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From a few years ago: General advice Both the papers sent to me appear to have strong research results. Now that the research has been done, I’d recommend rewriting both articles from scratch, using the following template: 1. Start with the conclusions. Write a couple pages on what you’ve found and what you recommend. In […]The post Advice on writing research articles appeared first on Statistical Modeling, Causal Inference, and…

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Real scientists make their own data

January 14, 2014
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Last week, I made the following statement: In theory, the availability of data should improve our ability to measure performance. In reality, the measurement revolution has not taken place. It turns out that measuring performance requires careful design and deliberate collection of the right types of data -- while Big Data is the processing and analysis of whatever data drops onto our laps. Ergo, we are far from fulfilling the…

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How many more R-bloggers posts can I expect?

January 14, 2014
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How many more R-bloggers posts can I expect?

I noticed that the monthly number of posts on R-bloggers stopped increasing over the last year. Indeed, the last couple of months saw a decline in posts compared to the previous year. Thus, has most been said and written about R already? Who knows? Wel...

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Applied Statistics Lesson of the Day – Positive Control in Experimental Design

Applied Statistics Lesson of the Day – Positive Control in Experimental Design

In my recent lesson on controlling for confounders in experimental design, the control group was described as one that received a neutral or standard treatment, and the standard treatment may simply be nothing.  This is a negative control group.  Not all experiments require a negative control group; some experiments instead have positive control group. A […]

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Why shouldn’t I dichotomize my outcome variable?

January 13, 2014
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My collaborators periodically want to dichotimize a continuous outcome such as a depression scale into a binary depressed/not depressed variable. Another popular one is Body Mass Index (BMI) gets classified into obese/not obese. Every time this arises...

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Job @ UCD

January 13, 2014
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This is an interesting job opportunity $-$ Mark (this is his UCL webpage, although he's now officially transitioned to Warwick) has pointed this out to me, and I thought I may as well advertise it through the blog!

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How to Find a Job in Statistics – Advice for Students and Recent Graduates

How to Find a Job in Statistics – Advice for Students and Recent Graduates

Introduction A graduate student in statistics recently asked me for advice on how to find a job in our industry.  I’m happy to share my advice about this, and I hope that my advice can help you to find a satisfying job and develop an enjoyable career.  My perspectives would be most useful to students […]

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Postdoc with Liz Stuart on propensity score methods when the covariates are measured with error

January 13, 2014
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Liz Stuart sends this one along: Johns Hopkins University Post-Doctoral Fellow Opening The Department of Mental Health invites applications for a post-doctoral research fellow in Statistical Methods for Mental Health Research, to be supervised by Dr. Elizabeth Stuart. The successful applicant for this position will work on an NIH funded study to develop and evaluate […]The post Postdoc with Liz Stuart on propensity score methods when the covariates are measured…

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How To Install BioPerl Without Root Privileges

January 13, 2014
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How To Install BioPerl Without Root Privileges

I've seen this question asked and partially answered all around the web. As with anything related to Perl, I'm sure there is more than one way to do it. Here's how I do it with Perl 5.10.1 on CentOS 6.4.First, install local::lib with bootstra...

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Judea Pearl overview on causal inference, and more general thoughts on the reexpression of existing methods by considering their implicit assumptions

January 13, 2014
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This material should be familiar to many of you but could be helpful to newcomers. Pearl writes: ALL causal conclusions in nonexperimental settings must be based on untested, judgmental assumptions that investigators are prepared to defend on scientific grounds. . . . To understand what the world should be like for a given procedure to […]The post Judea Pearl overview on causal inference, and more general thoughts on the reexpression…

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Announcement: Dataviz Workshop for Spring 2014

January 13, 2014
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I'm very excited to preview the syllabus of a new dataviz course I've been developing to be launched in Spring 2014. This course is focused on the craft of graph building, and is modeled after the writing workshop. Students will...

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garch models caught in the spotlight

January 13, 2014
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An attempt to clarify the basics. Previously There have been several posts about garch.  In particular: A practical introduction to garch modeling The components garch model in the rugarch package Genesis A reader emailed me because he was confused about the workings of garch in general, and simulation with the empirical distribution in particular. If … Continue reading →

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How to vectorize time series computations

January 13, 2014
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How to vectorize time series computations

Vector languages such as SAS/IML, MATLAB, and R are powerful because they enable you to use high-level matrix operations (matrix multiplication, dot products, etc) rather than loops that perform scalar operations. In general, vectorized programs are more efficient (and therefore run faster) than programs that contain loops. For an example [...]

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Sunday data/statistics link roundup (1/12/2014)

January 13, 2014
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Well it technically is Monday, but I never went to sleep so that still counts as Sunday right? As a person who has taught a couple of MOOCs I'm used to getting some pushback from people who don't like the … Continue reading →

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The State of Information Visualization, 2014

January 13, 2014
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The State of Information Visualization, 2014

2013 was another exciting year for visualization. Between many new developments in data storytelling, a new wave of news graphics, new visualization blogs, better automated infographics, and visuals designed to hit you hard, it is difficult to decide what was most important. Here is a look back, and some ideas about where we’re going. Storytelling […]

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MCMSki IV [mistakes and regrets]

January 12, 2014
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MCMSki IV [mistakes and regrets]

Now that the conference and the Bayesian non-parametric satellite workshop (thanks to Judith!) are over, with (almost) everyone back home, and that the post-partum conference blues settles in (!), I can reflect on how things ran for those meetings and what I could have done to improve them… (Not yet considering to propose a second […]

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Things that I like that almost nobody else is interested in

January 12, 2014
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This post by Jordan Ellenberg (“Stoner represents a certain strain in the mid-century American novel that I really like, and which I don’t think exists in contemporary fiction. Anguish, verbal restraint, weirdness”) reminds me that what I really like is mid-to-late-twentieth-century literary criticism. I read a great book from the 50s, I think it was, […]The post Things that I like that almost nobody else is interested in appeared first…

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The Extra Step: Graphs for Communication versus Exploration

January 12, 2014
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The Extra Step: Graphs for Communication versus Exploration

Visualization is a useful tool for data exploration and statistical analysis, and it’s an important method for communicating your discoveries to others. While those two uses of visualization are related, they aren’t identical. One of the reasons that I like ggplot so much is that it excels at layering together multiple views and summaries of […] Related posts: Revisiting Cleveland’s The Elements of Graphing Data in ggplot2 My Favorite Graphs…

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