Shiny app code for SolvoMediocris : http://shiny.dds.ec/solvomediocris/

server.R

library(shiny)
library(mc2d)
library(ggplot2)
library(scales)
 
shinyServer(function(input,output){
	
	values <- reactiveValues() 
	
	values$N <- 50000
	values$run <- "no"
	
	observe({
		
		if (input$runmodel != 0) {
			
			isolate({
				
				values$N <- input$N

				TEFestimate <- data.frame(L = input$tefl,  ML = input$tefml,  H = input$tefh, CONF = input$tefconf)
				TSestimate <- data.frame(L = input$tcapl,  ML = input$tcapml,  H = input$tcaph, CONF = input$tcapconf)
				RSestimate <- data.frame(L = input$csl,  ML = input$csml,  H = input$csh, CONF = input$csconf)
				LMestimate <- data.frame(L = input$lml, ML = input$lmml, H = input$lmh, CONF = 1)
		
				LMsample <- function(x){
				  return(sum(rpert(x, LMestimate$L, LMestimate$ML, LMestimate$H, shape = LMestimate$CONF) ))
				}
		
				TEFsamples <- rpert(values$N, TEFestimate$L, TEFestimate$ML, TEFestimate$H, shape = TEFestimate$CONF)
				TSsamples <- rpert(values$N, TSestimate$L, TSestimate$ML, TSestimate$H, shape = TSestimate$CONF)
				RSsamples <- rpert(values$N, RSestimate$L, RSestimate$ML, RSestimate$H, shape = RSestimate$CONF)
		
				VULNsamples <- TSsamples > RSsamples
				LEF <- TEFsamples[VULNsamples]
		
				values$ALEsamples <- sapply(LEF, LMsample)
				values$VAR <- quantile(values$ALEsamples, probs=(0.95))
				
			})

		}
		
	})
	
	output$detail <- renderPrint({
		if (input$runmodel != 0) {
			print(summary(values$ALEsamples));
		}
	})
	
	output$detail2 <- renderPrint({
		if (input$runmodel != 0) {
			print(paste0("Losses at 95th percentile are $", format(values$VAR, nsmall = 2, big.mark = ",")));
		}
	})
	
		  
	output$plot <- renderPlot({

		if (input$runmodel != 0) {
		
			ALEsamples <- values$ALEsamples 
						
			gg <- ggplot(data.frame(ALEsamples), aes(x = ALEsamples))
			gg <- gg + geom_histogram(binwidth = diff(range(ALEsamples)/50), aes(y = ..density..), color = "black", fill = "white")
			gg <- gg + geom_density(fill = "steelblue", alpha = 1/3)
			gg <- gg + scale_x_continuous(labels = comma)
			gg <- gg + theme_bw()
		
			print(gg)

		}	

	})
     
})

ui.R

shinyUI(pageWithSidebar(
	
    headerPanel("SolvoMediocris"),
		
    sidebarPanel(
			
			tags$head(
        tags$style(type="text/css", "input { font-size:10px; width:40px; display:inline-block; }"),
        tags$style(type="text/css", "#lml, #lmml, #lmh, #lmconf { font-size:11px; width:100px; display:inline-block; }"),
        tags$style(type="text/css", "#N { font-size:14px; width:200px; display:inline-block; }"),
        tags$style(type="text/css", "label[for=N] { font-size:14px; display:inline-block; }"),
        tags$style(type="text/css", "label { font-size:10px; display:inline-block; }")
			),
			
			h4("Threat Event Frequency"),
	    numericInput("tefl", "Min:", 10, min = 0, max = 100),
	    numericInput("tefml", "ML:", 20, min = 0, max = 100),
	    numericInput("tefh", "Max:", 100, min = 0, max = 100),
	    numericInput("tefconf", "Conf:", 1, min = 1, max = 5),
			
			h4("Threat Capability"),
	    numericInput("tcapl", "Min:", 20, min = 0, max = 100),
	    numericInput("tcapml", "ML:", 30, min = 0, max = 100),
	    numericInput("tcaph", "Max:", 70, min = 0, max = 100),
	    numericInput("tcapconf", "Conf:", 1, min = 1, max = 5),
			
			h4("Control Strength"),
	    numericInput("csl", "Min:", 40, min = 0, max = 100),
	    numericInput("csml", "ML:", 50, min = 0, max = 100),
	    numericInput("csh", "Max:", 60, min = 0, max = 100),
	    numericInput("csconf", "Conf:", 2, min = 1, max = 5),
			
			h4("Loss Magnitude"),
	    numericInput("lml", "Min:", 100, min = 0),
	    numericInput("lmml", "ML:", 500, min = 0), br(),
	    numericInput("lmh", "Max:", 10000, min = 0),
	    numericInput("lmconf", "Conf:", 1, min = 1, max = 5), br(),
	    
			numericInput("N", "# Iterations:", 50000, min = 1000, step=1000), br(),
			
			actionButton("runmodel", "Run Model"),
			
			div(HTML("<br/><small>(App brought to you by <a href='http://datadrivensecurity.info'>Data Driven Security</a>)</small>"))
			
    ),
		
    mainPanel(
        tabsetPanel(
            tabPanel("Distribution", plotOutput("plot")),
            tabPanel("Detail", verbatimTextOutput("detail"), verbatimTextOutput("detail2"))
        )
    )
		
))