1799 search results for "tutorial"

Singleton Remover CSV v0.3

April 21, 2014
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Singleton Remover CSV v0.3

I created a small program called Singleton Remover CSV to help researchers process files quickly that might otherwise take a long time to be handled by hand. The program simply compares ID values given in the first two columns of a .csv file, saves any...

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Free interactive R exercises on OpenIntro

April 21, 2014
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Free interactive R exercises on OpenIntro

DataCamp first to offer free interactive R tutorials via the OpenIntro platform. In one week, the ten-week Coursera course on Data Analysis and Statistical Inference by prof. Mine Çetinkaya-Rundel of Duke University comes to an end. At DataCamp it was one of our first experiences providing interactive R exercises on a large scale, and we’re proud to say

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Checking (G)LM model assumptions in R

April 16, 2014
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Checking (G)LM model assumptions in R

(Generalized) Linear models make some strong assumptions concerning the data structure: Independance of each data points Correct distribution of the residuals Correct specification of the variance structure Linear relationship between the response and the linear predictor For simple lm 2-4) means that the residuals should be normally distributed, the variance should be homogenous across the

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WrightMap 1.1 Ancillary Antelope Released

April 12, 2014
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WrightMap 1.1 Ancillary Antelope Released

The new version of WrightMap (Ancillary Antelope) is now available on CRAN. Remember that you can visit the package tutorials on our website. This new version includes: - New function to create fit graphs like the example below. - Parameter conversion: Function for calculating Thurstonian thresholds from Master’s deltas. - New examples. - Added axis range controls. - Made histogram...

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WrightMap 1.1 Ancillary Antelope Released

April 12, 2014
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WrightMap 1.1 Ancillary Antelope Released

The new version of WrightMap (Ancillary Antelope) is now available on CRAN. Remember that you can visit the package tutorials on our website. This new version includes: New function to create fit graphs like the example below. Parameter conversion: Function for calculating Thurstonian thresholds from Master’s deltas. New examples. Added axis...

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Shape File Selfies in ggplot2

April 11, 2014
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Shape File Selfies in ggplot2

In this post you will learn how to: Create your own quasi-shape file Plot your homemade quasi-shape file in ggplot2 Add an external svg/ps graphic to a plot Change a grid grob's color and alpha *Note get simple .md version … Continue reading →

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Side-by-Side Box Plots with Patterns From Data Sets Stacked by reshape2 and melt() in R

Side-by-Side Box Plots with Patterns From Data Sets Stacked by reshape2 and melt() in R

Introduction A while ago, one of my co-workers asked me to group box plots by plotting them side-by-side within each group, and he wanted to use patterns rather than colours to distinguish between the box plots within a group; the publication that will display his plots prints in black-and-white only.  I gladly investigated how to

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BARUG talks highlight R’s diverse applications

April 10, 2014
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BARUG talks highlight R’s diverse applications

by Joseph Rickert The seven lightning talks presented to the Bay Area useR Group on Tuesday night were not only really interesting (in some cases downright entertaining) in their own right, but they also illustrated the diversity of R applications, and the extent to which R has become embedded in the corporate world. Two presentations with a whimsical touch...

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Announcing our new training web pages

April 10, 2014
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Announcing our new training web pages

We’ve redesigned our training pages to make it even easier for you to learn R or Shiny. Visit our new training web page, www.rstudio.com/training, to see: A curated list of free materials for learning R. We think that these are some of the most helpful resources on the web. They would make an effective starting place

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Get notified when R packages update

April 8, 2014
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Get notified when R packages update

Today’s highly active R user base is developing, re-developing, and releasing R packages at a never-before-seen rate. While this is fantastic news for the R community as such, it inevitably also causes growing pains as mentioned before. One of the often cited problems is the painful and time-consuming task to keep track of changes and version updates of

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