Blog Archives

Laplace the Bayesianista and the Mass of Saturn

September 15, 2013
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Laplace the Bayesianista and the Mass of Saturn

I'm reviewing Bayes' theorem and related topics for the upcoming GDAT class. In its simplest form, Bayes' theorem is statement about conditional probabilities. The probability of A, given that B has occurred, is expressed as: \begin{equation} \Pr(A|B) = \dfrac{\Pr(B|A)\times\Pr(A)}{\Pr(B)} \label{eqn:bayes} \end{equation} In Bayesian language, $\Pr(A|B)$ is called the posterior probability, $\Pr(A)$ the prior probability, and $\Pr(B|A)$ the...

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GDAT Class October 14-18, 2013

August 25, 2013
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GDAT Class October 14-18, 2013

This is your fast track to enterprise performance analysis and capacity planning with an emphasis on applying R statistical tools to your performance data. Early-bird discounts are available for the Level III Guerrilla Data Analysis Techniques class O...

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Exponential Cache Behavior

May 15, 2013
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Exponential Cache Behavior

Guerrilla alumnus Gary Little observed certain fixed-point behavior in simulations where disk IO blocks are updated randomly in a fixed size cache. For his python simulation with 10 million entries (corresponding to an allocation of about 400 MB of memory) the following results were obtained: Hit ratio (i.e., occupied) = 0.3676748 Miss ratio...

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Adding Percentiles to PDQ

April 22, 2013
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Adding Percentiles to PDQ

Pretty Damn Quick (PDQ) performs a mean value analysis of queueing network models: mean values in; mean values out. By mean, I mean statistical mean or average. Mean input values include such queueing metrics as service times and arrival rates. These could be sample means. Mean output values include such queueing metrics as waiting time and queue...

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Upcoming GDAT Class May 6-10, 2013

April 22, 2013
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Upcoming GDAT Class May 6-10, 2013

Enrollments are still open for the Level III Guerrilla Data Analysis Techniques class to be held during the week May 6—10. Early-bird discounts are still available. Enquire when you register. As usual, all classes are held at our lovely Larkspur...

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Extracting the Epidemic Model: Going Beyond Florence Nightingale Part II

February 7, 2013
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Extracting the Epidemic Model: Going Beyond Florence Nightingale Part II

This is the second of a two part reexamination of Florence Nightingale's data visualization based on her innovative cam diagrams (my term) shown in Figure 1. Figure 1. Nightingale's original cam diagrams (click to enlarge)RecapIn Part I, I showed that FN applied sectoral areas, rather than a pie chart or...

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Going Beyond Florence Nightingale’s Data Diagram: Did Flo Blow It with Wedges?

January 23, 2013
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Going Beyond Florence Nightingale’s Data Diagram: Did Flo Blow It with Wedges?

In 2010, I wrote a short blog item about Florence Nightingale the statistician, solely because of its novelty value. I didn't even bother to look closely at the associated graphic she designed, but that's what I intend to do here. In this first installment, I reflect on her famous data visualization by reconstructing it...

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The Social Network Ranking is Wrong

January 14, 2013
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The Social Network Ranking is Wrong

Call me old-fashioned, but I never saw the movie The Social Network until last year (at a private screening). In case you also missed it, it's the Hollywood version of how Facebook.com came into being. Quite apart from any artistic criticisms, I have a genuine psychological problem with movies like TSN. I keep getting caught up...

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PDQ 6.0.1 is Released

December 18, 2012
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PDQ 6.0.1 is Released

As already described previously, the main purpose of Release 6.0.1 Build 121512 is improved compatibility and stability between PDQ and the R statistical environment. For example, many of the PDQ models, previously found in the ../examples/ directory, can now also be accessed via the demo() command in the R-console. Testing was carried out using R version...

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PDQ 6.0 is On Its Way

November 12, 2012
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PDQ (Pretty Damn Quick) version 6.0.β is in the QA pipeline. Although this is a major release, cosmetically, things won't look any different when it comes to writing PDQ models. All the big changes have taken place under the hood in order to make PDQ more consistent with the R statistical environment. R version 2.15.2...

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