Publications by Posts on Tychobra
Simulating Insurance Claims
When I was fresh out of college, my boss asked me to run some simulations in R. This was my first exposure to R, and I was initially skeptical of its practical usefulness. But with some Googling and a little perseverence, I overcame the initial frustrations and am now about the biggest R fanboy around. It turns out that random simulations served ...
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Example Shiny App – Interest Rate Walk
This Shiny app demonstrates the Cox-Ingersoll-Ross interest rate walk and an interest rate walk conducted using a bootstrap resampling technique. The code used to create this app is available on GitHub. Assuming you have the necessary packages installed, you should be able to run this Shiny app on your local computer. A live version of the app is...
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Atlanta R Users Presentation
These are the slides from my presentation at the April Atlanta R User meetup. There are not many words on the slides, so you won’t be able to follow the presentation by flipping through the slides. I nonetheless wanted to share them because the presentation uses the ioslides Rmarkdown template to directly embed Shiny applications into the prese...
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shinyFeedback 0.1.0 on CRAN
Version 0.1.0 of the shinyFeedback package is now available on CRAN. You can install the latest version by running: install.packages("shinyFeedback") The shinyFeedback package makes it easy to display useful feedback notifications in Shiny apps. Since the initial shinyFeedback CRAN release, it has been able to display short messages, icons, and c...
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Machine Learning for Insurance Claims
We are pleased to announce a new demo Shiny application that uses machine learning to predict annual payments on individual insurance claims for 10 years into the future. This post describes the basics of the model behind the above Shiny app, and walks through the model fitting, prediction, and simulation ideas using a single claim as an example...
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How to build your own Neural Network from scratch in R
Last week I ran across this great post on creating a neural network in Python. It walks through the very basics of neural networks and creates a working example using Python. I enjoyed the simple hands on approach the author used, and I was interested to see how we might make the same model using R. In this post we recreate the above-mentioned Py...
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Adding Firebase Authentication to Shiny
Firebase and Shiny Firebase is a mobile and web application development platform owned by Google. Firebase provides front-end solutions for authentication, database storage, object storage, messaging, and more. Firebase drastically reduces the time needed to develop certain types of highly scalable and secure applications. As heavy R users, Shiny...
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Excel Report Generation with Shiny
R is great for report generation. Shiny allows us to easily create web apps that generate a variety of reports with R. This post details a demo Shiny app that generates an Excel report, a PowerPoint report, and a PDF report: The full Shiny app source code is available here. Also, we included a more basic Shiny app that generates an Excel report a...
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PowerPoint Report Generation with Shiny
In this post we generate a PowerPoint report from a Shiny app. This is Part 2 from the 3-post series about generating reports with Shiny. Part 1 covered Excel Report Generation with Shiny. See part 1 for a quick intro and description of the Shiny app that can generate Excel, PowerPoint, and PDF reports. PowerPoint Report These are the slides fro...
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Polished – Modern Authentication for Shiny
We are excited to announce polished. Polished is a new R package that adds modern user authentication and user administration to your Shiny apps. Polished comes with many of the authentication features required by today’s web apps (e.g. user registration, password reset, email verification, role-based authorization, etc.). Polished is availabl...
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