Monthly Archives: September 2012

Minimum Correlation Algorithm Example

September 23, 2012
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Minimum Correlation Algorithm Example

Today I want to follow up with the Minimum Correlation Algorithm Paper post and show how to incorporate the Minimum Correlation Algorithm into your portfolio construction work flow and also explain why I like the Minimum Correlation Algorithm. First, let’s load the ETF’s data set used in the Minimum Correlation Algorithm Paper using the Systematic

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Video: Analyzing Big Data using Oracle R Enterprise

September 23, 2012
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Learn how Oracle R Enterprise is used to generate new insight and new value to business, answering not only what happened, but why ...

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Football model; plots and usage

September 23, 2012
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Football model; plots and usage

After reading data, making a predictions display and building a football data model it is time to put this to validate a bit more (regression plots) and put to usage. It appears that the regression plots in the car package were not ...

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Project Euler — problem 20

September 23, 2012
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It’s been quite a while since my last post on Euler problems. Today a visitor post his solution to the second problem nicely, which encouraged me to keep solving these problems. Just for fun! 10! = 10 * 9 * … * 3 * 2 * 1 … Continue reading →

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The infamous apply function

September 23, 2012
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The infamous apply function

For R beginners, the apply() function seems like a secret doorway into programming bliss. It seems so powerful, and yet, beyond reach. For those just starting out, examples of how to use apply() can really help with the intuition of how to h...

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Text Analysis Tutorial on Spam Email in R

September 23, 2012
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Text Analysis Tutorial on Spam Email in R

Hi everyone – I just wrote a tutorial on text analysis in R using the tm and wordcloud packages. Thought some of you here might be interested in it: text-analysis-75-925

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Maximum likelihood estimates for multivariate distributions

September 22, 2012
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Maximum likelihood estimates for multivariate distributions

Consider our loss-ALAE dataset, and - as in Frees & Valdez (1998) - let us fit a parametric model, in order to price a reinsurance treaty. The dataset is the following, > library(evd) > data(lossalae) > Z=lossalae > X=Z;Y=Z ...

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Spacing measures: heterogeneity in numerical distributions

Spacing measures: heterogeneity in numerical distributions

Numerically-coded data sequences can exhibit a very wide range of distributional characteristics, including near-Gaussian (historically, the most popular working assumption), strongly asymmetric, light- or heavy-tailed, multi-modal, or discrete (e.g., count data).  In addition, numerically coded values can be effectively categorical, either ordered, or unordered.  A specific example that illustrates the range of distributional behavior often seen in a collection...

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Maximum likelihood estimates for multivariate distributions

September 22, 2012
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Maximum likelihood estimates for multivariate distributions

Consider our loss-ALAE dataset, and – as in Frees & Valdez (1998) - let us fit a parametric model, in order to price a reinsurance treaty. The dataset is the following, > library(evd) > data(lossalae) > Z=lossalae > X=Z;Y=Z The first step can be to estimate marginal distributions, independently. Here, we consider lognormal distributions for both components, > Fempx=function(x) mean(X<=x) >...

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Good programming practices in R

September 22, 2012
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I write sloppy R scripts. It is a byproduct of working with a high-level language that allows you to quickly write functional code on the fly (see this post for a nice description of the problem in Python code) and the result of my limited formal training in computer programming. The lack of formal training

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