I have the following error appearing when running R Shiny:
Listening on http://127.0.0.1:7473
Warning: Error in :: argument of length 0
Stack trace (innermost first):
76: renderPlot [C:\Users\voroneci\Documents\Dissertation\Projecting Swaption Vol\Log Normal Vol Projector App - Using PR2/server.R#162]
68: output$lognormal2
1: shiny::runApp
App does run locally, however when deploying on shinyapps.io it greys out with the classic message of server being disconnected, I am assuming it is due to this error.
server.R:
require(shiny,quietly = TRUE)
require(forecast,quietly = TRUE)
require(rsconnect,quietly = TRUE)
options(shiny.maxRequestSize=30*1024^2)
load("./PR2.RData")
load("./F1.RData")
load("./F2.RData")
load("./all_data_lognormal.RData")
load("./R.RData")
load("./sigma.RData")
load("./mu.RData")
shinyServer(function(input, output, session) {
output$lognormal <- renderPlot({
all_data <- all_data[all_data$LogNormalVol>0,]
all_data$LogNormalVol <- (log10(all_data$LogNormalVol)+1)/0.1
if(is.null(input$run) |is.na(input$run) ){
return()
}else{
input$run
ahead <- isolate(input$ahead)
paths <- isolate(input$paths)
und_ <- isolate(input$Underlying)
exp_ <- isolate(input$Expiry)
str_ <- isolate(input$Strike)
seed <- isolate(input$seed)
imp <- subset(all_data,all_data$UND==und_)
imp <- subset(imp ,imp$EXP==exp_)
imp <- subset(imp ,imp$Strike==str_)
imp <- imp[!duplicated(imp$Date),]
imp <- imp$LogNormalVol/100
set.seed(seed)
estimate.I <- ts(replicate(paths, simulate(model1.3, nsim=ahead, xreg = 1259+1:ahead ,future = TRUE)),start=1259+1)
estimate.II <- ts(replicate(paths, simulate(model2.3, nsim=ahead, xreg = 1259+1:ahead ,future = TRUE)),start=1259+1)
predicted.vol <-c()
for(i in 1:paths){
projected.PCs <- cbind(estimate.I[,i],estimate.II[,i])
reconstructed.F <- projected.PCs%*%t(R)[1:2,]
reconstructed.F_scaled <- matrix(rep(mu,times=nrow(reconstructed.F)),byrow=TRUE,ncol=14) + reconstructed.F * matrix(rep(sigma,times=nrow(reconstructed.F)),byrow=TRUE,ncol=14)
predict.df <- data.frame(Date=c(1:ahead),
LogNormalVol=rep(NA,times=length(c(1:ahead))),
UND = as.numeric(rep(und_,times=length(c(1:ahead)))),
EXP = as.numeric(rep(exp_,times=length(c(1:ahead)))),
Strike = as.numeric(rep(str_,times=length(c(1:ahead)))),
F1 =reconstructed.F_scaled[,1] ,
F2 =reconstructed.F_scaled[,2] ,
F3 =reconstructed.F_scaled[,3] ,
F4 =reconstructed.F_scaled[,4] ,
F5 =reconstructed.F_scaled[,5] ,
F6 =reconstructed.F_scaled[,6] ,
F7 =reconstructed.F_scaled[,7] ,
F8 =reconstructed.F_scaled[,8] ,
F9 =reconstructed.F_scaled[,9] ,
F10=reconstructed.F_scaled[,10],
F11=reconstructed.F_scaled[,11],
F12=reconstructed.F_scaled[,12],
F13=reconstructed.F_scaled[,13],
F14=reconstructed.F_scaled[,14])
predicted.vol2 <- predict(PR2,newdata=predict.df)
predicted.vol <- rbind(predicted.vol,predicted.vol2)
}
predicted.vol <-(predicted.vol+1)/0.1
predicted.vol <- predicted.vol/100
all <- cbind(matrix(rep(imp,times=paths),nrow=paths,byrow=TRUE),predicted.vol)
ylim <- c(min(all),
max(all))
for(i in 1:paths){
if(i==1){
if(length(imp)==0){
plot(c(0,1),c(0,1),type="n", xlab="",ylab="", xaxt='n', yaxt='n')
legend(0.15,0.6,"Data not available",cex=1.5)
}else{
plot(imp,type="l",xlim=c(0,(length(imp)+ahead)),ylab="Log-Normal Vol", xlab="Steps",cex.lab=0.8,lty=1,lwd=2,col="darkblue",ylim=ylim,
main="Zoom In Plot")
#legend("topleft",c("Observed","Projected"),col=c("darkblue","darkgreen"),lty=1)
}
}
lines(c((length(imp)+1):(length(imp)+ahead)),predicted.vol[i,],col=i,lty=i,lwd=1)
lines(c(length(imp),length(imp)+1),c(imp[length(imp)],predicted.vol[i,1]),col=i,lty=i,lwd=1)
}
}
})
output$lognormal2 <- renderPlot({
all_data <- all_data[all_data$LogNormalVol>0,]
all_data$LogNormalVol <- (log10(all_data$LogNormalVol)+1)/0.1
if(is.null(input$zoom) |is.na(input$zoom) ){
return()
}else{
input$zoom
ahead <- isolate(input$ahead)
paths <- isolate(input$paths)
und_ <- isolate(input$Underlying)
exp_ <- isolate(input$Expiry)
str_ <- isolate(input$Strike)
seed <- isolate(input$seed)
imp <- subset(all_data,all_data$UND==und_)
imp <- subset(imp ,imp$EXP==exp_)
imp <- subset(imp ,imp$Strike==str_)
imp <- imp[!duplicated(imp$Date),]
imp <- imp$LogNormalVol/100
set.seed(seed)
estimate.I <- ts(replicate(paths, simulate(model1.3, nsim=ahead, xreg = 1259+1:ahead ,future = TRUE)),start=1259+1)
estimate.II <- ts(replicate(paths, simulate(model2.3, nsim=ahead, xreg = 1259+1:ahead ,future = TRUE)),start=1259+1)
predicted.vol <-c()
for(i in 1:paths){
projected.PCs <- cbind(estimate.I[,i],estimate.II[,i])
reconstructed.F <- projected.PCs%*%t(R)[1:2,]
reconstructed.F_scaled <- matrix(rep(mu,times=nrow(reconstructed.F)),byrow=TRUE,ncol=14) + reconstructed.F * matrix(rep(sigma,times=nrow(reconstructed.F)),byrow=TRUE,ncol=14)
predict.df <- data.frame(Date=c(1:ahead),
LogNormalVol=rep(NA,times=length(c(1:ahead))),
UND = as.numeric(rep(und_,times=length(c(1:ahead)))),
EXP = as.numeric(rep(exp_,times=length(c(1:ahead)))),
Strike = as.numeric(rep(str_,times=length(c(1:ahead)))),
F1 =reconstructed.F_scaled[,1] ,
F2 =reconstructed.F_scaled[,2] ,
F3 =reconstructed.F_scaled[,3] ,
F4 =reconstructed.F_scaled[,4] ,
F5 =reconstructed.F_scaled[,5] ,
F6 =reconstructed.F_scaled[,6] ,
F7 =reconstructed.F_scaled[,7] ,
F8 =reconstructed.F_scaled[,8] ,
F9 =reconstructed.F_scaled[,9] ,
F10=reconstructed.F_scaled[,10],
F11=reconstructed.F_scaled[,11],
F12=reconstructed.F_scaled[,12],
F13=reconstructed.F_scaled[,13],
F14=reconstructed.F_scaled[,14])
predicted.vol2 <- predict(PR2,newdata=predict.df)
predicted.vol <- rbind(predicted.vol,predicted.vol2)
}
predicted.vol <-(predicted.vol+1)/0.1
predicted.vol <- predicted.vol/100
all <- cbind(matrix(rep(imp,times=paths),nrow=paths,byrow=TRUE),predicted.vol)
xlim <- isolate(input$range)
ylim <- c(min(all[,isolate(input$range)[1]:(isolate(input$range)[2]-1)]),
max(all[,isolate(input$range)[1]:(isolate(input$range)[2]-1)]))
for(i in 1:paths){
if(i==1){
if(length(imp)==0){
plot(c(0,1),c(0,1),type="n", xlab="",ylab="", xaxt='n', yaxt='n')
legend(0.15,0.6,"Data not available",cex=1.5)
}else{
plot(imp,type="l",xlim=xlim,ylab="Log-Normal Vol", xlab="Steps",cex.lab=0.8,lty=1,lwd=2,col="darkblue",ylim=ylim,
main="Zoom In Plot")
#legend("topleft",c("Observed","Projected"),col=c("darkblue","darkgreen"),lty=1)
}
}
lines(c((length(imp)+1):(length(imp)+ahead)),predicted.vol[i,],col=i,lty=i,lwd=1)
lines(c(length(imp),length(imp)+1),c(imp[length(imp)],predicted.vol[i,1]),col=i,lty=i,lwd=1)
}
}
})
output$Range <- renderUI({
if(is.na(input$ahead)|is.null(input$ahead)){
return()
}else{
ahead <- input$ahead
und_ <- input$Underlying
exp_ <- input$Expiry
str_ <- input$Strike
imp <- subset(all_data,all_data$UND==und_)
imp <- subset(imp ,imp$EXP==exp_)
imp <- subset(imp ,imp$Strike==str_)
imp <- imp[!duplicated(imp$Date),]
imp <- imp$LogNormalVol/100
ahead <- input$ahead
sliderInput("range", "Step Range Zoom In", min=1, max = length(imp)+ahead, value=c(length(imp)-50,length(imp)+ahead),step=1)
}
})
})
ui.R:
library(shiny)
library(markdown)
library(shinythemes)
require(rsconnect,quietly = TRUE)
shinyUI(fluidPage(title="Swaption Implied Vol Projector",
theme = shinytheme("cerulean"),
fluidRow(
column(3, h2("Swaption Implied Vol Predictor"),
h3("Log Normal Vols"),
numericInput("ahead", label = "Number of Steps", value = 252),
numericInput("paths", label = "Number of Paths", value = 1),
numericInput("seed" , label = "Random Seed" , value = 1)
),
column(9,
mainPanel(
plotOutput("lognormal")
)
)
),
fluidRow(
column(3,
selectInput("Underlying", label = "Underlying (Years):",
choices = c(1,2,3,4,5,6,7,8,9,10,15,20,25,30), selected =10),
selectInput("Expiry", label ="Expiry (Years):",
choices = c(1/12,3/12,6/12,1,2,3,4,5,7,10,15,20,25,30), selected =10),
selectInput("Strike", label ="Strike (%):",
choices = c(-2.5,-2,-1.5,-1,-0.5,0,0.5,1,1.5,2,2.5), selected =0),
p(actionButton("run",
"Run simulation", icon("random"))),
uiOutput("Range"),
p(actionButton("zoom",
"Zoom In!"))
),
column(9,
mainPanel(
tags$style(type="text/css",
".shiny-output-error { visibility: hidden; }",
".shiny-output-error:before { visibility: hidden; }"
),
plotOutput("lognormal2")
))
)
))
Can anyone spot what am I missing?
Thank you!
Best Answer
Maybe you can try
req(input$run)instead of using:For more information, you can refer to RStudio's article on
req.