1972 search results for "ggplot"

R code for Chapter 2 of Non-Life Insurance Pricing with GLM

March 13, 2012
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R code for Chapter 2 of Non-Life Insurance Pricing with GLM

We continue working our way through the examples, case studies, and exercises of what is affectionately known here as “the two bears book” (Swedish björn = bear) and more formally as Non-Life Insurance Pricing with Generalized Linear Models by Esbjörn Ohlsson and Börn Johansson (Amazon UK | US). At...

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In case you missed it: February Roundup

March 13, 2012
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In case you missed them, here are some articles from February of particular interest to R users. February 29 marked the 12th anniversary of the release of R 1.0.0, and the release of R 2.14.2. A list of commercial vendors who have integrated R with their products for data, analysis, and presentation. The rmr package (part of the RHadoop...

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R index between two products is somewhat dependent on other products

March 12, 2012
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R index between two products is somewhat dependent on other products

I explained earlier how R-index is used in sensory is used to examine ranking data. The legitimization to use R-index is in the link with d' and with Mann-Whitney statistic. In this post I show there is a dependence on the number of products and p...

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Compiling government positions from the Manifesto Project data with R

March 12, 2012
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Compiling government positions from the Manifesto Project data with R

The Manifesto Project (former Manifesto Research Group, Comparative Manifestos Project) has assembled a database of ‘quantitative content analyses of parties’ election programs from more than 50 countries covering all free, democratic elections since 1945′ and is freely accessible online. The … Continue reading →

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The R-Podcast Episode 3: Basic Interaction with R

March 11, 2012
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In this episode: New versions of R and ggplot2 available, listener feedback, and an interactive session with R. The R code discussed in this episode will be available in our GitHub repository, see the show notes for details. There will be a companion screencast to accompany this episode which will be posted shortly. As always,

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Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

March 9, 2012
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Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

In the last post I presented a function for recovering marginal effects of interaction terms. Here we implement the function with simulated data and plot the results using ggplot2.       #---Simulate Data and Fit a linear model with an...

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Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

March 9, 2012
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Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

In the last post I presented a function for recovering marginal effects of interaction terms. Here we implement the function with simulated data and plot the results using ggplot2.       #---Simulate Data and Fit a linear model with an...

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Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

March 9, 2012
By
Recovering Marginal Effects and Standard Errors of Interactions Terms Pt. II: Implement and Visualize

In the last post I presented a function for recovering marginal effects of interaction terms. Here we implement the function with simulated data and plot the results using ggplot2.       #---Simulate Data and Fit a linear model with an...

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Mining Twitter for consumer attitudes towards hotels

March 9, 2012
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Mining Twitter for consumer attitudes towards hotels

Couple of months back I read Jeffrey Breen’s presentation on mining Twitter for consumer attitudes towards airlines, so I was just curious how it would look if I estimate the sentiment toward major hotels. So here it is: # load twitter library > library(twitteR) # search for all the hilton tweets > hilton.tweets=searchTwitter('@hilton',n=1500) > length(hilton.tweets)

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Benford’s Law after converting count data to be in base 5

March 8, 2012
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Benford’s Law after converting count data to be in base 5

Firstly, I know nothing about election fraud – this isn’t a serious post. But, I do like to do some simple coding. Ben Goldacre posted on using Benford’s Law to look for evidence of Russian election fraud. Then Richie Cotton did the same, but using R. Commenters on both sites suggested that as the data

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