Beta Error

server.R

library(shiny)
library(ggplot2)
library(gridExtra)
library(scales)
library(reshape2)
library(zoo)


shinyServer(function(input, output) {
  output$distribution <- renderPlot({
        SD <- input$SD
        mean.pop <- 0
        mean.sample <- mean.pop + input$diff.mean
        max.x <- input$max
        min.x <- input$min
        alpha <- input$alphaValue
        beta <- qnorm(alpha,mean=mean.pop,sd=SD,lower.tail=FALSE)#input$betaValue
        pts <- 100
        
        x <- seq(min.x,max.x,length.out=pts)
        pop <- dnorm(x,mean=mean.pop,sd=SD)
        smp <- dnorm(x,mean=mean.sample,sd=SD)
        
        ndata <- data.frame(x,pop,smp)
        nplot <- ggplot(data=ndata,aes(x=x)) + ylab("P(x)") + geom_line(aes(y=pop)) + geom_line(aes(y=smp))
        
        alphazone <- subset(ndata, pnorm(x,mean=mean.pop,sd=SD,lower.tail=FALSE) <= alpha)
        betazone <- subset(ndata, x <= min(alphazone$x))
        
        if (length(row.names(alphazone))){
          nplot <- nplot + geom_ribbon(aes(x=x,ymin=0,ymax=pop), data=alphazone, fill="blue",alpha=0.5)
        }
        
        if (length(row.names(betazone))){
          nplot <- nplot +geom_ribbon(aes(x=x,ymin=0,ymax=smp), data=betazone, fill="red",alpha=0.5)
        }
        
        print(nplot)
        
  })
})

ui.R

library(shiny)

# Define UI for application that draws a histogram
shinyUI(fluidPage(
  titlePanel("The relationship of significance level (alpha) to beta error"),
  
  sidebarLayout(
    sidebarPanel(h2("Experimental Parameters")
                 ,  sliderInput("alphaValue"
                                ,"Significance / Sensitivity Threshold"
                                ,min = 0.01
                                ,max = 1.0
                                ,value = 0.05)
                , numericInput("max"
                             ,"Max x to plot"
                             ,value = 10)
                , numericInput("min"
                               ,"min x to plot"
                               ,value = -10)
                , numericInput("SD"
                               ,"standard deviation"
                               ,value = 1)
                , numericInput("diff.mean"
                                 ,"True difference in means"
                                 ,value = 1)
     )
    ,mainPanel(h2("Hits and misses at a given significance level.")
               ,plotOutput("distribution")
                ,p("Blue is correctly detected, red is incorrectly dismissed.")
              )
  )
  
 
))