3798 search results for "GIS"

caret webinar on Feb 25

February 2, 2014
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I"ll be doing a webinar with the Orange County R User Group on the caret package on Tue, Feb 25, 2014 1:00 PM - 2:00 PM EST.Here is the url in case you are interested: https://www3.gotomeeting.com/register/673845982Thanks to Ray DiGiacom...

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New d3.js visualization: Understanding Significance Testing and Statistical Power

February 2, 2014
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New d3.js visualization: Understanding Significance Testing and Statistical Power

Here is a new visualization created in the same manner as my Cohen’s d vizualisation. This new visualization is an interactive display of classical null hypothesis significance testing and statistical power. The visualization should work on mobile phones and tablets, but it requires a modern browser that supports SVG. Check...

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Boxplot with mean and standard deviation in ggPlot2 (plus Jitter)

February 2, 2014
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Boxplot with mean and standard deviation in ggPlot2 (plus Jitter)

When you create a boxplot in R, it automatically computes median, first and third quartile ("hinges") and 95% confidence interval of median ("notches").But we would like to change the default values of boxplot graphics with the mean, the mean + st...

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Bayesian analysis of sensory profiling data

February 2, 2014
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Bayesian analysis of sensory profiling data

I looked at Bayesian analysis of sensory profiling data in May and June 2012. I do remember not being totally happy with the result and computations taking a bit more time than I wanted. But now it is 2014, I can use STAN and I have been thinking about...

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Know India through Visualisations – 1

February 1, 2014
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Know India through Visualisations – 1

I'm going to produce just a couple of charts, a teaser of sorts in this post. In the forthcoming posts I'll dig deeper.I was amazed with the existing list of R packages to work with spatial data, without needing to get into much of the technical detail...

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Bad Bayes: an example of why you need hold-out testing

February 1, 2014
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Bad Bayes: an example of why you need hold-out testing

We demonstrate a dataset that causes many good machine learning algorithms to horribly overfit. The example is designed to imitate a common situation found in predictive analytic natural language processing. In this type of application you are often building a model using many rare text features. The rare text features are often nearly unique k-grams Related posts:

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ShareLaTeX now supports knitr

January 31, 2014
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ShareLaTeX (click here to register a free account) is a wonderful and reliable on-line editor for writing and compiling LaTeX documents “in the cloud” as well as working together in real-time (imagine Google Docs supporting LaTeX => you get ShareLaTeX).…Read more ›

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Python and R: Is Python really faster than R?

January 30, 2014
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A friend of mine asked me to code the following in R:Generate samples of size 10 from Normal distribution with $\mu$ = 3 and $\sigma^2$ = 5;Compute the $\bar{x}$ and $\bar{x}\mp z_{\alpha/2}\displaystyle\frac{\sigma}{\sqrt{n}}$ using the 95% confidence...

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Comparing multiple (g)lm in one graph #rstats

January 29, 2014
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Comparing multiple (g)lm in one graph #rstats

It’s been a while since a user of my plotting-functions asked whether it would be possible to compare multiple (generalized) linear models in one graph (see comment). While it is already possible to compare multiple models as table output, I now managed to build a function that plots several (g)lm-objects in a single ggplot-graph. The

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Analyzing Sleep with Sleep Cycle App and R

January 28, 2014
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Analyzing Sleep with Sleep Cycle App and R

I have been tracking my sleep for almost two years now using my Fitbit. I started with the Fitbit Ultra and then moved on the the Fitbit One after it came out. In October 2013 I found out about the Sleep Cycle (Link) app for the iPhone. For weeks, Sleep Cycle was listed as the … Continue reading...

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