2678 search results for "gis"

The Failure of Asset Allocation – Bonds Are An Imperfect Hedge

July 24, 2012
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The Failure of Asset Allocation – Bonds Are An Imperfect Hedge

US investors were spoiled by US Treasuries which acted as a near perfect hedge to stocks during the 2008-2009 crisis.  However, in real crisis, bonds rarely offer any comfort, and asset allocation fails (see post Death Spiral of a Country and IMF ...

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What’s wrong with LOESS for palaeo data?

July 24, 2012
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What’s wrong with LOESS for palaeo data?

Locally weighted scatterplot smoothing (LOWESS) or local regression (LOESS) is widely used to highlight “signal” in variables from stratigraphic sequences. It is a user-friendly way of fitting a local model that derives its form from the data themselves rather than having … Continue reading →

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What’s wrong with LOESS for palaeo data?

July 24, 2012
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What’s wrong with LOESS for palaeo data?

Locally weighted scatterplot smoothing (LOWESS) or local regression (LOESS) is widely used to highlight “signal” in variables from stratigraphic sequences. It is a user-friendly way of fitting a local model that derives its form from the data themselves rather than having to be specified a priori by the user. There are generally two things that a user has...

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Deploy Rook Apps with rApache: Part I

July 23, 2012
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Since rApache 1.1.15 you’ve been able to deploy you Rook applications like so: # Run the Rook application named 'app'. On each request, the expression # 'Rook::Server$call(app)' is evaluated in an environment populated by # rookapp.R. 'app' is expected to be found in that environment. <Location /test/RookApp> SetHandler r-handler ...

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Modeling Trick: Impact Coding of Categorical Variables with Many Levels

July 23, 2012
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Modeling Trick: Impact Coding of Categorical Variables with Many Levels

One of the shortcomings of regression (both linear and logistic) is that it doesn’t handle categorical variables with a very large number of possible values (for example, postal codes). You can get around this, of course, by going to another modeling technique, such as Naive Bayes; however, you lose some of the advantages of regression Related posts:

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Third year wrap-up

July 23, 2012
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Third year wrap-up

July marks the end of three years of blogging for us. By our count, we've posted 121 examples across the first three years. We aim to be helpful and interesting.As always, it's hard to get a sense of our readership. At the time we wrote this, Feedbur...

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London Olympics and a prediction for the 100m final

July 22, 2012
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London Olympics and a prediction for the 100m final

It is less than a week before the 2012 Olympic games will start in London. No surprise therefore that the papers are all over it, including a lot of data and statistis around the games. The Economist investigated the potential financial impact on spons...

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Modeling Permanent and Gradual Process Changes with CDFs

July 20, 2012
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Modeling Permanent and Gradual Process Changes with CDFs

Spencer HerathSpecial thanks to Ben OgorekBackgroundI recently faced a process with a structural change resulting in an increase in the process mean.  The jump to the new mean was not immediate; rather, there was a gradual increase in values over time.  I had previously benefited from multi-staged process-behavior charts when encountering immediate process shifts, but now I needed a...

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Best of Axys, R, d3.js, and HTML5

July 19, 2012
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Best of Axys, R, d3.js, and HTML5

Axys, R, d3.js, and HTML5 all offer incredibly powerful tools for investment management and reporting, but they are not set up to synergistically interact to fill each other’s gaps and leverage each other’s strengths.  In my ideal scenario, Ax...

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Plotting the Frequency of Twitter Hashtag Usage Over Time with R and ggplot2

July 17, 2012
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Plotting the Frequency of Twitter Hashtag Usage Over Time with R and ggplot2

The 20th annual ISMB meeting was held over the last week in Long Beach, CA. It was an incredible meeting with lots of interesting and relevant talks, and lots of folks were tweeting the conference, usually with at least a few people in each concurrent ...

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