262 search results for "pca"

read raster data in parallel

August 18, 2012
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read raster data in parallel

Use library(parallel) to read raster data in parallel fashion Use library(parallel) to read raster data in parallel fashion Recently, I have been doing some analysis for a project I am involved in. In particular, I was...

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Adventures at My First JSM (Joint Statistical Meetings) #JSM2012

August 6, 2012
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Adventures at My First JSM (Joint Statistical Meetings) #JSM2012

During the past few decades that I have been in graduate school (no, not literally) I have boycotted JSM on the notion that “I am not a statistician.” Ok, I am a renegade statistician, a statistician by training. JSM 2012 was held in San Diego, CA, one of the best places to spend a week during the summer. This...

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Discriminating Between Iris Species

August 4, 2012
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Discriminating Between Iris Species

The Iris data set is a famous for its use to compare unsupervised classifiers. The goal is to use information about flower characteristics to accurately classify the 3 species of Iris. We can look at scatter plots of the 4 variables in the data set and see that no single variable nor bivariate combination can achieve this. One approach to improve the separation

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Archetypal Analysis

July 30, 2012
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Archetypal Analysis

Thinking Strategically about Customer HeterogeneityIronically, market segmentation, whose motto is "one size does not fit all," seems to rely almost exclusively on one definition of what constitutes a segment.  Borrowing its definition f...

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Color Palettes in RGB Space

June 20, 2012
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Color Palettes in RGB Space

Introduction I've recently been interested in how to communicate information using color. I don't know much about the field of Color Theory, but it's an interesting topic to me. The selection of color palettes, in particular, has been a topic I've been faced with lately. I downloaded 18 different sequential color palettes from Cynthia Brewer's

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Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks.

June 13, 2012
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Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks.

AbstractVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods—multiple linear regression and artificial neural networks—that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods,...

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Stepping Outside My Open-Source Comfort Zone: A First Look at Golden Helix SVS

May 16, 2012
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Stepping Outside My Open-Source Comfort Zone: A First Look at Golden Helix SVS

I'm a huge supporter of the Free and Open Source Software movement. I've written more about R than anything else on this blog, all the code I post here is free and open-source, and a while back I invited you to steal this blog under a cc-by-sa license....

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Visualising the Path of a Genetic Algorithm

April 23, 2012
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Visualising the Path of a Genetic Algorithm

We quite regularly use genetic algorithms to optimise over the ad-hoc functions we develop when trying to solve problems in applied mathematics. However it’s a bit disconcerting to have your algorithm roam through a high dimensional solution space while not being able to picture what it’s doing or how close one solution is to another. … Continue reading...

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Customising vegan’s ordination plots

April 11, 2012
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Customising vegan’s ordination plots

As a developer on the vegan package for R, one of the most FAQs is how to customise ordination diagrams, usually to colour the sample points according to an external grouping variable. Now, just because we get asked how to … Continue reading →

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Customising vegan’s ordination plots

April 11, 2012
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Customising vegan’s ordination plots

As a developer on the vegan package for R, one of the most FAQs is how to customise ordination diagrams, usually to colour the sample points according to an external grouping variable. Now, just because we get asked how to do this a lot is not really a reflection on the quality of the plot() methods...

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