R Shiny

This is a simple integration of ChatGPT into shiny R. At first I wanted to do this in Python but it was easier to do a web app in R Shiny. I used code from this site to get started: https://www.listendata.com/2023/05/chatgpt-in-r.html#steps_to_run_chatgpt_in_r The app is hosted at: https://twong.shinyapps.io/chat_bot/ The R code for this shiny app is below. library(shiny) library(httr) ui <- fluidPage( titlePanel("ChatGPT Shiny App"), textInput("user_input", "Enter your message:"), actionButton("submit_btn", "Submit"), p(""), textOutput("chat_output"), p(""), p("Code for this page is at https://codelooper. [Read More]

This page is made using code from: https://github.com/semanzi/fitting_distributions_with_R_NHSR_2021/tree/main

The app is hosted at: https://twong.shinyapps.io/HSMA_distr_tool/

I just learned that I could embed the R Shiny app into blogdown from this post. So here’s an attempt at that.

When I was working with stop loss reinsurance contracts the usual way to perform the pricing exercise would be to gather all the loss data, fit a loss distribution to that data, make adjustments based on seasonal outlook or other variables, and apply the limits and retentions asked by the clients/brokers. Although this is standard practice and almost second nature, another way to look at the pricing problem is from the point of view that you, as an underwriter, do not have all the information and perhaps should take into consideration market pricing. [Read More]