833 search results for "how to import image file to R"

useR 2012: main conference braindump

June 24, 2012
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useR 2012: main conference braindump

I knew R was versatile, but DANG, people do a lot with it: > > … I don’t think anyone actually believes that R is designed to make *everyone* happy. For me, R does about 99% of the things I … Continue reading →

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Learning a new language

June 21, 2012
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Learning a new language

It had been a very long time since I’d tried to learn a new programming language. I started C in 1987, S in 1992, and Perl in 1997, but nothing really new in the subsequent 15 years. A friend now has me doing D, wanting to find time to learn ruby, and, most recently, playing

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Confidence intervals with tiers: functions for between-subjects (independent measures) ANOVA

June 21, 2012
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Confidence intervals with tiers: functions for between-subjects (independent measures) ANOVA

In a previous post I showed how to plot difference-adjusted CIs for between-subjects (independent measures) ANOVA designs (see here). The rationale behind this kind of graphical display is introduced in Chapter 3 of Serious stats (and summarized in my earlier blog post). In a between-subjects – or in indeed in a within-subjects (repeated measures) – design

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My first "ChemoSpec" spectra

June 21, 2012
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My first "ChemoSpec" spectra

I’ve been this week trying to import some spectra to ChemoSpec (R Package), at the beginning I had problems generating the “csv”  files, and the function getManyCsv did not recognize the files. I did not have properly configured the regional...

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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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Finding word use patterns in Wikileaks cables

June 12, 2012
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Finding word use patterns in Wikileaks cables

6/18: A follow-up to this post is now available here.Recent DiscoveriesWhen I was a diplomat, I was always interested in the Wikileaks cables and what could be done with them. Unfortunately, I never got a chance to look at the site in depth, due to security policies. Now that the ex- is firmly prepended to diplomat...

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Finding word use patterns in Wikileaks cables

June 12, 2012
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Finding word use patterns in Wikileaks cables

6/18: A follow-up to this post is now available here.Recent DiscoveriesWhen I was a diplomat, I was always interested in the Wikileaks cables and what could be done with them. Unfortunately, I never got a chance to look at the site in depth, due to security policies. Now that the ex- is firmly prepended to diplomat...

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Finding Word Use Patterns in Wikileaks Cables

June 12, 2012
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Finding Word Use Patterns in Wikileaks Cables

6/18: A follow-up to this post is now available here.Recent DiscoveriesWhen I was a diplomat, I was always interested in the Wikileaks cables and what could be done with them. Unfortunately, I never got a chance to look at the site in depth, due to security policies. Now that the ex- is firmly prepended to diplomat in my...

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Data distillation with Hadoop and R

June 11, 2012
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Data distillation with Hadoop and R

We're definitely in the age of Big Data: today, there are many more sources of data readily available to us to analyze than there were even a couple of years ago. But what about extracting useful information from novel data streams that are often noisy and minutely transactional ... aye, there's the rub. One of the great things about...

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