I am attempting to generate a plot using variables in my server code that can be changed- I’m not sure if I am formatting this wrong and that is why a plot is not generating. My goal is to generate a line plot depending on a change in the ‘mean sojourn time’ and ‘screen sensitivity’ (these are my input widgets)- a change in this variable impact the values of x and y in my line plot. I want to be able to visualize how changing these variables will change the line plot.

This is my current code:

library(shiny)
library(tidyverse)
ui <- fluidPage(numericInput(inputId = 'y',
                  label = 'Mean Sojourn Time',
                  value = '5',
                  min = '1'),
                numericInput(inputId = 'pr',
                             label = 'Screen Senst',
                             value = '0',
                             min = '0',
                             max = '1',
                             step = '0.25'),
                plotOutput(outputId = 'lineplot')
                )

server <- function(input,output) {
  output$lineplot <- renderPlot({
  t_0 <- 40 
  startage <- 50
  n <- 100000
  k <- 30
  x <- 0.58
  lambda <- -(log(1-x))/k 
  y <- input$y
  mu <- 1/y
  num.screen <- 1:10
  pr <- input$pr
  
  counter <- 2
  repeat{
    id <- c()
    t_p <- t_0 + rexp(n, lambda)
    t_c <- t_p + rexp(n, mu)
    
    newdf <- data.frame(t_p, t_c) %>% 
      filter (t_c <= 100)
    cancerdf <- mutate(newdf, id = row_number()) %>% 
      select(id, everything()) 
    
    result <- reframe(cancerdf, screen.num = num.screen,.by = id)
    ddset <- cancerdf %>% 
      right_join(result, by= id) %>% 
      mutate(screen.age = screen.num + startage - 1) %>%
      filter(t_c > startage,
             t_c > screen.age) %>%
      filter(t_c > screen.age | t_c-screen.age <= 1) 
    ddset$test.result = rbinom(nrow(ddset), 1, prob = pr)
    
    new.ddset <- ddset %>% 
      filter(cumsum(test.result)<=1  
             & test.result==cummax(test.result), .by=id) %>%
      filter(t_p < screen.age, t_c > screen.age) %>% 
      group_by(id) %>%
      mutate(screen = (ifelse(test.result == 1 & t_c > screen.age, 1,0))) %>% 
      mutate(interval = ifelse(t_c - screen.age > 1, 0,1 ),
             interval = ifelse(screen == 1 & interval == 1, 0,interval)) 
    
    simulation.sensitivity <- new.ddset %>% 
      group_by(screen.age) %>% 
      summarise(screen = (sum(screen)),
                interval = (sum(interval)),
                sensitivity = (screen/ (screen + interval)))
    counter <- counter - 1
    if (counter == 0) {
      break
    }
simulation.sensitivity %>% 
  ggplot(aes(x = screen.age, y= sensitivity)) +
    geom_point() +
    geom_smooth(method = 'lm', se = FALSE)+
    theme_minimal()
  }})
}
shinyApp(ui=ui, server=server)

I don’t get an error, but no plot is rendering.