<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/"></div></div><div><a data-url="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/" data-counturl="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/" data-count="horizontal" data-text="Heuristica: An R package for testing models of binary choice" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="http://www.decisionsciencenews.com/2016/08/03/heuristica-r-package-testing-models-binary-choice/"> R – Decision Science News</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>CLASSIC HEURISTICS AND DATA SETS ALL IN ONE TIDY PACKAGE</p>
<p><a target="_blank" rel="attachment wp-att-5807" href="http://www.decisionsciencenews.com/2016/08/03/heuristica-r-package-testing-models-binary-choice/shtmus/"><img alt="shtmus" class="wp-image-5807" src="https://i0.wp.com/www.decisionsciencenews.com/wp-content/uploads/2016/08/shtmus.jpg?resize=388%2C568" data-recalc-dims="1"></a>
</p>
<p>It just got a lot easier to simulate the performance of simple heuristics.</p>
<p>Jean Whitmore, a software engineer at Google with a long history in modeling cognition, and Daniel Barkoczi, a postdoctoral fellow at the Max Planck Institute for Human Development, have created <a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/">heuristica</a>: an <a target="_blank" href="https://cran.r-project.org/">R</a> package to model the performance of simple heuristics. It comprises the heuristics covered in the first chapters of <a target="_blank" href="http://amzn.to/2agRk6u">Simple Heuristics That Make Us Smart</a> such as Take The Best, Unit Weighted Linear model, and more. The package also includes data, such as the the original German cities data set which has become a benchmark for testing heuristic models of choice, cited in hundreds of papers.</p>
<p>A good place to start is the <a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/vignettes/README.html">README </a>vignette, as with vignettes:</p>
<ul>
<li><a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/vignettes/cross-validation.html">Comparing the performance of simple heuristics using the Heuristica R package</a></li>
<li><a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/vignettes/how-to-make-heuristic.html">How to make your own heuristic</a></li>
<li><a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/vignettes/reproducing-results.html">Reproducing Results</a> (Take The Best vs. regression on city population)</li>
</ul>
<p>Here’s the <a target="_blank" href="https://cran.r-project.org/web/packages/heuristica/index.html">heuristica package’s home on CRAN</a> and here’s a description of the package in the authors’ own words:</p>
<blockquote><p>The heuristica R package implements <a target="_blank" href="http://en.wikipedia.org/wiki/Heuristic">heuristic</a> decision models, such as <a target="_blank" href="http://en.wikipedia.org/wiki/Take-the-best_heuristic">Take The Best</a> (TTB) and a <a target="_blank" href="http://en.wikipedia.org/wiki/Unit-weighted_regression">unit-weighted linear model</a>. The models are designed for two-alternative choice tasks, such as which of two schools has a higher drop-out rate. The package also wraps more well-known models like regression and logistic regression into the two-alternative choice framework so all these models can be assessed side-by-side. It provides functions to measure accuracy, such as an overall <code>percentCorrect</code> and, for advanced users, some <a target="_blank" href="https://en.wikipedia.org/wiki/Confusion_matrix">confusion matrix</a> functions. These measures can be applied in-sample or out-of-sample.</p>
<p>The goal is to make it easy to explore the range of conditions in which simple heuristics are better than more complex models. Optimizing is not always better!</p>
</blockquote>
<p>The post <a target="_blank" rel="nofollow" href="http://www.decisionsciencenews.com/2016/08/03/heuristica-r-package-testing-models-binary-choice/">Heuristica: An R package for testing models of binary choice</a> appeared first on <a target="_blank" rel="nofollow" href="http://www.decisionsciencenews.com/">Decision Science News</a>.</p>
<p><div><div><div><div data-width="55" data-show-faces="false" data-send="true" data-layout="box_count" data-height="62" data-href="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/"></div></div><div><a data-url="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/" data-counturl="https://www.r-bloggers.com/heuristica-an-r-package-for-testing-models-of-binary-choice/" data-count="vertical" data-text="Heuristica: An R package for testing models of binary choice" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.decisionsciencenews.com/2016/08/03/heuristica-r-package-testing-models-binary-choice/"> R – Decision Science News</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a title="The R Project for Statistical Computing" rel="nofollow" href="https://www.r-project.org/">R</a> news and <a title="R tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=tutorial">tutorials</a> on topics such as: <a title="Data science" rel="nofollow" href="https://www.r-bloggers.com/?s=data%20science">Data science</a>, <a title="Big Data" rel="nofollow" href="https://www.r-bloggers.com/?s=Big%20Data">Big Data, <a title="R jobs" rel="nofollow" href="https://www.r-users.com/">R jobs</a>, visualization (<a title="ggplot and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=ggplot2">ggplot2</a>, <a title="Boxplots using lattice and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=boxplot">Boxplots</a>, <a title="Maps and gis" rel="nofollow" href="https://www.r-bloggers.com/?s=map">maps</a>, <a title="Animation in R" rel="nofollow" href="https://www.r-bloggers.com/?s=animation">animation</a>), programming (<a title="RStudio IDE for R" rel="nofollow" href="https://www.r-bloggers.com/?s=RStudio">RStudio</a>, <a title="Sweave and literate programming" rel="nofollow" href="https://www.r-bloggers.com/?s=sweave">Sweave</a>, <a title="LaTeX in R" rel="nofollow" href="https://www.r-bloggers.com/?s=LaTeX">LaTeX</a>, <a title="SQL and databases" rel="nofollow" href="https://www.r-bloggers.com/?s=SQL">SQL</a>, <a title="Eclipse IDE for R" rel="nofollow" href="https://www.r-bloggers.com/?s=eclipse">Eclipse</a>, <a title="git and github, Version Control System" rel="nofollow" href="https://www.r-bloggers.com/?s=git">git</a>, <a title="Large data in R using Hadoop" rel="nofollow" href="https://www.r-bloggers.com/?s=hadoop">hadoop</a>, <a title="Web Scraping of google, facebook, yahoo, twitter and more using R" rel="nofollow" href="https://www.r-bloggers.com/?s=Web+Scraping">Web Scraping</a>) statistics (<a title="Regressions and ANOVA analysis tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=regression">regression</a>, <a title="principal component analysis tutorial" rel="nofollow" href="https://www.r-bloggers.com/?s=PCA">PCA</a>, <a title="Time series" rel="nofollow" href="https://www.r-bloggers.com/?s=time+series">time series</a>, <a title="finance trading" rel="nofollow" href="https://www.r-bloggers.com/?s=trading">trading</a>) and more...
<img height="1" alt="" width="1" src="http://feeds.feedburner.com/~r/RBloggers/~4/OoLwvD9GVuo"></a></div>