I have this code and I want to have a Select Input option to select from two different ways of plotting the graphic.
I want that if you choose the "level" option "fit 2" gets plotted instead of just fit.
this is fit2.
plot(forecast(fit2,
#Confidence Interval %
level = c(70,90)),
sub= "Confidence Interval 70% ~ 90%
or Determined by user",
ylab= "Y Axis Variable",
main= "Forecast Linear Structural Model @ Level-Wise",
ylim = c(0,400))
This is the Shiny code.
library(forecast)
library(shiny)
timese <- ts(WWWusage, start= c(2008,1), end= c(2016,1), frequency=12)
fit <- StructTS(timese,"trend")
fit2 <- StructTS(timese,"level")
ui <- fluidPage(
(titlePanel("app | Forecast Models", windowTitle = "app")),
#Select input
selectInput(inputId = "select", label = "Select Forecast",
choices = c("Trend","Level"),
plotOutput(outputId = "hist")),
#Range Input
sliderInput(inputId = "range",
label = "Set Confidence Interval. Up to 99%",
min = 0,max = 99, value = c(60,90)),
mainPanel(plotOutput(outputId = "plot"))
)
server <- function(input, output) {
output$plot <- renderPlot({
plot(forecast(fit, #Confidence Interval %
level = c(input$range)),
sub= "Confidence Interval 70% ~ 90% or Determined by user",
ylab= "Y Axis Variable",
main= "Forecast Linear Structural Model @ Trend-Wise",
ylim = c(0,400))
})
}
shinyApp(ui, server)
Like
server <- function(input, output) {
output$plot <- renderPlot({
if(input$select=="Trend")
plot(forecast(fit, #Confidence Interval %
level = c(input$range)),
sub= "Confidence Interval 70% ~ 90% or Determined by user",
ylab= "Y Axis Variable",
main= "Forecast Linear Structural Model @ Trend-Wise",
ylim = c(0,400))
else
plot(forecast(fit2,
#Confidence Interval %
level = c(70,90)),
sub= "Confidence Interval 70% ~ 90% or Determined by user",
ylab= "Y Axis Variable",
main= "Forecast Linear Structural Model @ Level-Wise",
ylim = c(0,400))
})
}
Basically you'd decide based on the input$select what to plot inside render plot.
A slightly more elegant version would be.
server <- function(input, output) {
output$plot <- renderPlot({
if(input$select=="Trend")
method <- fit
else
method <- fit2
plot(forecast(method, #Confidence Interval %
level = c(input$range)),
sub= "Confidence Interval 70% ~ 90% or Determined by user",
ylab= "Y Axis Variable",
main= "Forecast Linear Structural Model @ Trend-Wise",
ylim = c(0,400))
})
}
However, this makes the two plot "more similar". As you can see in title. So you would need to define additional vars in the if. This comes down to a trade off