server.R

library(shiny)
library(ggvis)

colors <- c('black','red','green','grey')
shinyServer(function(input, output,session) {
	population0 <- reactive({
		data.frame(Value = rnorm(n = 100000,mean = input$mu0,sd = input$sigma0))
	})
	
	population1 <- reactive({
		data.frame(Value = rnorm(n=100000,mean = input$mu1, sd = input$sigma1))
	})
	subsample <- function(d,ssize){
		ind <- sample(1:nrow(d),size = ssize, replace = TRUE)
		mean(d[ind,'Value'])
	}	
	samplingDist0 <- reactive({
#		invalidateLater(input$refresh,session = session);
		ds0 <- population0()
		data.frame(Means = replicate(n = input$sNum,expr = subsample(ds0,input$ssize)))
	})
	samplingDist1 <- reactive({
		ds1 <- population1()
		data.frame(Means = replicate(n = input$sNum, expr = subsample(ds1,input$ssize)))
	})
	
	samplingDists <- reactive({
		s0 <- samplingDist0()
		s1 <- samplingDist1()
		ds <- data.frame(Means = rbind(s0,s1), group = rep(c('Null','Effect'),each=input$sNum))
		ds
	})
	
	gv <- reactive({
		ggvis(samplingDists(),
		      by_group(factor(group)),
		      props(x = ~Means, 
		           fillOpacity := input_slider(min = 0,
		           			    max = 1,
		           			    value = .7,
		           			    step = .1,
		           			    label = 'Opacity')),
		      layer_histogram())
#			dscale('x','numeric',domain=c(-5,5))  +
#			guide_axis('x',title='Sample Mean') + 
#			guide_axis('y',title="Frequency")
			
	})
	
	output$samplingDist <- observe_ggvis(gv, 'samplingDist', session)
	output$plotControls <- renderControls(gv, session)
	
})

ui.R

library(shiny)

shinyUI(pageWithSidebar(
  
  # Application title
  headerPanel("Distribution of sample means"),
  
  # Sidebar with a slider input for number of observations
  sidebarPanel(
    sliderInput("sigma0", 
                "Null Population Standard Deviation", 
                min = .01, 
                max = 10, 
                value = 1,
    	    	step = .05),
    sliderInput("mu0",
    	    	"Null Population Mean",
    	    	min = -10,
    	    	max = 10,
    	    	value = 0,
    	    	step = 1),
    sliderInput('sigma1',
    	    	'Effect Population Standard Deviation',
    	    	min = .01,
    	    	max = 10,
    	    	value = 1,
    	    	step = .05),
    sliderInput('mu1',
    	    	'Effect Population Mean',
    	    	min = -10,
    	    	max = 10,
    	    	value = 0,
    	    	step = 1),
    sliderInput("sNum",
    	    	"Number of samples",
    	    	min = 1,
    	    	max = 10000,
    	    	value = 100,
    	    	step = 2),
    sliderInput("ssize",
    	    	"Sample Size",
    	    	min = 5,
    	    	max = 1000,
    	    	value = 20,
    	    	step = 5),
    numericInput('refresh',
    	     	min = 500,
    	     	max = 60000,
    	     	label = 'Refresh rate (ms)',
    	     	value = 3000)
  ),
  
  # Show a plot of the generated distribution
  mainPanel(
  	ggvis_output('samplingDist'),
  	ggvisControlOutput('plotControls')
  )
))