Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Introduction Today, I will discuss the alpha decay of americium-241 and use R to model the number of emissions from a real data set with the Poisson distribution.  I was especially intrigued in learning about the use of Am-241 in smoke detectors, and I will elaborate on this clever application.  I will then use the Pearson chi-squared

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Datasets handpicked by students

April 14, 2013
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I’m often on the hunt for datasets that will not only work well with the material we’re covering in class, but will (hopefully) pique students’ interest. One sure choice is to use data collected from the students, as it is … Continue reading →

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BayesComp homepage

April 14, 2013
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BayesComp homepage

Today, the BayesComp section of ISBA launched its website. It is organised as a wiki and members of the section are strongly incited to take part into the construction of the website. To quote from Peter Green’s introduction: This new Wikidot site aims to be a community-edited resource on all aspects of Bayesian computation, available

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Win Your Snake Draft: Calculating “Value Over Replacement” using R

April 14, 2013
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Win Your Snake Draft: Calculating “Value Over Replacement” using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com and how to calculate players’ risk levels. In this post, I will demonstrate how to win your snake The post Win Your Snake Draft: Calculating "Value Over Replacement" using R appeared first on Fantasy Football Analytics.

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Win Your Snake Draft: Calculating “Value Over Replacement” using R

April 14, 2013
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Win Your Snake Draft: Calculating “Value Over Replacement” using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com and how to calculate players' risk levels. In this post, I will demonstrate how...

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PSID data set builder for R

April 14, 2013
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Economists frequently use public datasets. One frequently used dataset is the Panel Study of Income Dynamics, short PSID, maintained by the Institute of Social Research at the University of Michigan.I'm introducing psidR, which is a small helper packag...

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Predicting Dichotomous Outcomes I

April 14, 2013
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Predicting Dichotomous Outcomes I

We are trying to predict a dependent dichotomous variable (male/female, yes/no, like/dislike,etc) with independent “predictor” variables. Let’s say we want to determine whether or not an employee will quit based on the percentage of their tenure spent traveling. We assemble the data from HR and erroneously employ simple linear regression to model the relationship, a

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Using R — Working with Geospatial Data

April 14, 2013
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Using R — Working with Geospatial Data

This entry is part 6 of 12 in the series Using RGIS, an acronym that brings joy to some and strikes fear in the heart of those not interested in buying expensive software. Luckily fight or flight can be saved for another day because you …   read more ...

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Tip: Julia vs. R – introduction videos and more

April 14, 2013
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Last years UseR 2012 conference in Nashville had an interesting discussion session titled “What other languages should R users know about?“. General consensus was that multilingualism is inevitable in modern computing, and panel members presented various languages that complement R in different ways. Some of the usual suspects included SQL, python, and of course C++, ...

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Continuing Sync

April 14, 2013
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Continuing Sync

I am continuing in Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Lifeby Steven Strogatz. To get a feeling on it, I was building a group of things which have only a minute influence on each other are able to synchronize thei...

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Benchmarking Machine Learning Models Using Simulation

April 13, 2013
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Benchmarking Machine Learning Models Using Simulation

What is the objective of most data analysis? One way I think about it is that we are trying to discover or approximate what is really going on in our data (and in general, nature). However, I occasionally run into people think that if one model fulfills our expectations (e.g. higher number of significant p-values or accuracy) than it...

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Using ddply to select the first record of every group

April 13, 2013
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Using ddply to select the first record of every group

I had a very long file of monetary transactions (about 207,000 rows) with about two handfuls of columns describing each transaction (including date).  The task I needed to perform on this file was to select the value from one of … Continue reading →

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Webinar Follow-Up: First Batch of Answers to Overflow Questions

April 13, 2013
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We’re delighted with the response to our webinar, Big Analytics for R Users without Big Hassles. Attendees were engaged and we didn’t have time to answer all the questions submitted through the chat window. We’ll answer the overflow questions in batches. Here’s the first batch. Is SciDB performance optimized for 2D arrays and 3D arrays?

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Motivating Students

April 13, 2013
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Motivating Students

Figure shown to students in a particular class to show the effect of slacking after the mid-semester grades are received.Background information: A course has multiple components - Exams, projects, quizzes, assignments, etc. The objective of this set of...

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knitr documents with tikzDevice graphics

April 13, 2013
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Setting up tikzDevice output in knitr may be a frustrating task, but gives outstandingly aesthetic, LaTeX-like figures. Here are my global knitr settings for typesetting documents in Polish (in UTF-8, make sure your R also runs in a Unicode locale…Read more ›

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Configure Kile for knitr under GNU/Linux

April 13, 2013
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Kile – a convenient LaTeX editor – may also be used to prepare knitr-generated reports. Here is how we may make our work much more efficient with a convenient compile-on-keypress feature. Create a bash script in your home directory, named…Read more ›

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Classification Tree Models

Classification Tree Models

On March 26, I attended the Connecticut R Meetup in New Haven, which featured a talk by Illya Mowerman on decision trees in R.  I have gone to these Meetups before, and I have always found them to be interesting and informative.  Attendees range from those who are just starting to explore R to those who have multiple CRAN...

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Spring Cleaning Data: 6 of 6- Saving the Data

April 13, 2013
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With all the cleaning done, the only thing left to do is save the data to be analyzed, for future use, and I hope by others. The data I thought would be simple, but there were a few interesting twist, like the Primary Credit*, and using ifelse() to edi...

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Calculate Fantasy Players’ Risk Levels using R

April 12, 2013
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Calculate Fantasy Players’ Risk Levels using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com. In this post, I will demonstrate how to calculate fantasy The post Calculate Fantasy Players’ Risk Levels using R appeared first on Fantasy Football Analytics.

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Calculate Fantasy Players’ Risk Levels using R

April 12, 2013
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Calculate Fantasy Players’ Risk Levels using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com. In this post, I will demonstrate how to calculate fantasy football players' risk levels.  Just like when determin...

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Mathematical abstraction and the robustness to assumptions

April 12, 2013
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Mathematical abstraction and the robustness to assumptions

I’ve been showing my new favourite toys to just about anyone foolish enough to actually engage me in conversation. I described how my shiny new set of non-transitive dice work here, complete with a map showing all the relevant probabilities. All was neat and tidy and wonderful until fellow ecologist, Aaron Ball, tried to burst

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Stan 1.3.0 and RStan 1.3.0 Ready for Action

April 12, 2013
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Stan 1.3.0 and RStan 1.3.0 Ready for Action

The Stan Development Team is happy to announce that Stan 1.3.0 and RStan 1.3.0 are available for download. Follow the links on: Stan home page: http://mc-stan.org/ Please let us know if you have problems updating. Here’s the full set of release notes. v1.3.0 (12 April 2013) ====================================================================== Enhancements ---------------------------------- Modeling Language * forward sampling (random The post Stan...

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Extending RevoScaleR for Mining Big Data – Discretization

April 12, 2013
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Extending RevoScaleR for Mining Big Data – Discretization

by Derek McCrae Norton, Senior Sales Engineer In this second installment of Extending RevoScaleR for Mining Big Data we look at how to use the building blocks provided by RevoScaleR to transform continuous variables into discrete. Motivation: Discretize continuous variables on big data. Discretization is a technique to convert continuous variables into discrete variables, and it is sometimes useful...

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Spring Cleaning Data: 5 of 6- 2 ifelse vs Merge

April 12, 2013
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The blog in the data cleaning series looks at separating out the Federal Reserve Districts. What I wanted was two additional columns, where I had the name of the city and the number for each district. Since I was on a separation kick I thought it would...

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Using the RcppArmadillo-based Implementation of R’s sample()

April 12, 2013
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Using the RcppArmadillo-based Implementation of R’s sample()

Overview and Motivation All of R’s (r*, p*, q*, d*) distribution functions are available in C++ via the R API. R is written in C, and the R API has no concept of a vector (at least not in the STL sense). Consequently, R’s sample() function can’t just be exported via the R API, despite its importance and usefulness....

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Using the RcppArmadillo-based Implementation of R’s sample()

April 12, 2013
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Using the RcppArmadillo-based Implementation of R’s sample()

Overview and Motivation All of R’s (r*, p*, q*, d*) distribution functions are available in C++ via the R API. R is written in C, and the R API has no concept of a vector (at least not in the STL sense). Consequently, R’s sample() function can’t just be exported via the R API, despite its importance and usefulness....

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Travis CI for R! (not yet)

April 12, 2013
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Travis CI for R! (not yet)

A few days ago I wrote about Travis CI, and was wondering if we could integrate the testing of R packages into this wonderful platform. A reader (Vincent Arel-Bundock) pointed out in the comments that Travis was running Ubuntu that allows you to install software packages at your will. I took a look at the documentation, and realized...

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Processing ABI .fsa files in R, part 1.

April 11, 2013
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Processing ABI .fsa files in R, part 1.

I’ve been working on a lot of AFLP data this winter. I’d really like to be able to do all the analysis in R, for a few reasons. First, it would mean no more fighting with GeneMapper, which is incredibly frustrating: it’s Windows-only, expensive, closed-source and painfully underpowered for the job. Second, presumably if I

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Download File from Google Drive/Docs Programmatically with R

April 11, 2013
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Following up my lattest posting on how to download files from the cloud with R..dl_from_GoogleD ## Arguments:## output = output file name## key = Google document key## format = output format (pdf, rtf, doc, txt..)## Note: File must be shareable! ...

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