Early warning signals shiny program for use in R

server.R

library(shiny)
library(Kendall)

shinyServer(function(input, output) {
  output$tsplot <- renderPlot({
		table <- read.table('tip.txt')
		ts <- table[,1]
		tscut <- ts[1:input$cut]
		smoothed <- ksmooth(c(1:input$cut),tscut,bandwidth=input$bw,x.points=c(1:input$cut))
		detrend <- tscut - smoothed$y
		plot(ts,type="l",ylab='X')
		lines(smoothed,col='red')
		lines(c(input$cut,input$cut),c(-100,100),lty=3)
					})
	output$ar1plot <- renderPlot({
		table <- read.table('tip.txt')
		ts <- table[,1]
		tscut <- ts[1:input$cut]
		smoothed <- ksmooth(c(1:input$cut),tscut,bandwidth=input$bw,x.points=c(1:input$cut))
		detrend <- tscut - smoothed$y
		ar1 <- rep(NA, (length(ts)-input$wl))
		for (i in 1:(input$cut-input$wl)) {
			arfit <- ar.ols(detrend[i:(i+input$wl)], aic=FALSE, order.max=1)
			ar1[i] <- arfit$ar
						}
		kend <- Kendall(c(1:length(ar1)),ar1)
		plot(c(input$wl:(input$wl-1+length(ar1))),ar1,type="l", main=paste('AR(1): Tau=',format(kend$tau, digits=3),sep=""), xlim=c(1,length(ts)),xlab='Index',ylab='AR(1)')
					})
	output$variplot <- renderPlot({
		table <- read.table('tip.txt')
		ts <- table[,1]
		tscut <- ts[1:input$cut]
		smoothed <- ksmooth(c(1:input$cut),tscut,bandwidth=input$bw,x.points=c(1:input$cut))
		detrend <- tscut - smoothed$y
		vari <- rep(NA, (length(ts)-input$wl))
		for (i in 1:(input$cut-input$wl)) {
			vari[i] <- var(detrend[i:(i+input$wl)])
						}
		kend <- Kendall(c(1:length(vari)),vari)
		plot(c(input$wl:(input$wl-1+length(vari))),vari,type="l", main=paste('Variance: Tau=',format(kend$tau,digits=3),sep=""),xlim=c(1,length(ts)),xlab='Index',ylab='Variance')
					})

	})

timeseries.R

x <- seq(-2,2,by=0.01)  		#x axis for plotting
mu <- 2*sqrt(3)/9			#bifurcation parameter
t <- seq(1,1000,by=1)			#time steps
m <- mu*t/900				#the change in the bifurcation parameter over time (this is the length of t compared to mu which is a single value)

a <- rep(NA, (length(t)+1))		#setting up vector to hold created time series
a[1] <- -1				#start it in the left well

for (i in 1:length(m)) {
	      a[i+1] <- a[i] + (1/2)*(-a[i]^3+a[i]+m[i]) + 0.1*rnorm(1)
			}

write.table(a,file='tip.txt',col.names=FALSE,row.names=FALSE)

ui.R

library(shiny)

# Define UI for miles per gallon application
shinyUI(pageWithSidebar(

  # Application title
  headerPanel("Early Warning Signals"),

  sidebarPanel(
  
	sliderInput("bw","Detrending Bandwidth:",min=0.5,max=50,value=10),
	sliderInput("wl","Window Length:",min=250,max=650,value=425),
	numericInput("cut", "Cut-off point:", 875)
			),

  mainPanel(
	plotOutput("tsplot"),
	plotOutput("ar1plot"),
	plotOutput("variplot")	
			)
))