shinyapp of "retirement simulation" does not work for me

[synchro]

Hi my professors

I tried to test this shiny application retirement-simulation , but i think that i make a mistake.
off course i did some modification on the code, but i think that i didnt do all modifications due to my beginner level in R.
Please help me to identify my mistake .

Thank you very much my family

library(shiny)

renderInputs <- function(prefix) {
  wellPanel(
    fluidRow(
      column(6,
             sliderInput(paste0(prefix, "_", "n_obs"), "Number of observations (in Years):", min = 0, max = 40, value = 20),
             sliderInput(paste0(prefix, "_", "start_capital"), "Initial capital invested :", min = 100000, max = 10000000, value = 2000000, step = 100000, pre = "$", sep = ","),
             sliderInput(paste0(prefix, "_", "annual_mean_return"), "Annual investment return (in %):", min = 0.0, max = 30.0, value = 5.0, step = 0.5),
             sliderInput(paste0(prefix, "_", "annual_ret_std_dev"), "Annual investment volatility (in %):", min = 0.0, max = 25.0, value = 7.0, step = 0.1)
      ),
      column(6,
             sliderInput(paste0(prefix, "_", "annual_inflation"), "Annual inflation (in %):", min = 0, max = 20, value = 2.5, step = 0.1),
             sliderInput(paste0(prefix, "_", "annual_inf_std_dev"), "Annual inflation volatility. (in %):", min = 0.0, max = 5.0, value = 1.5, step = 0.05),
             sliderInput(paste0(prefix, "_", "monthly_withdrawals"), "Monthly capital withdrawals:", min = 1000, max = 100000, value = 10000, step = 1000, pre = "$", sep = ","),
             sliderInput(paste0(prefix, "_", "n_sim"), "Number of simulations:", min = 0, max = 2000, value = 200)
      )
    ),
    p(actionButton(paste0(prefix, "_", "recalc"),
                   "Re-run simulation", icon("random")
    ))
  )
}

# Define UI for application that plots random distributions
ui <- fluidPage(theme="simplex.min.css",
          tags$style(type="text/css",
                     "label {font-size: 12px;}",
                     ".recalculating {opacity: 1.0;}"
          ),
          
          # Application title
          tags$h2("Retirement: simulating wealth with random returns, inflation and withdrawals"),
          p("An adaptation of the",
            tags$a(href="https://systematicinvestor.wordpress.com/2013/04/06/retirement-simulating-wealth-with-random-returns-inflation-and-withdrawals-shiny-web-application/", "retirement app"),
            "from",
            tags$a(href="http://systematicinvestor.wordpress.com/", "Systematic Investor"),
            "to demonstrate the use of Shiny's new grid options."),
          hr(),
          
          fluidRow(
            column(6, tags$h3("Scenario A")),
            column(6, tags$h3("Scenario B"))
          ),
          fluidRow(
            column(6, renderInputs("a")),
            column(6, renderInputs("b"))
          ),
          fluidRow(
            column(6,
                   plotOutput("a_distPlot", height = "600px")
            ),
            column(6,
                   plotOutput("b_distPlot", height = "600px")
            )
          )
)
paramNames <- c("start_capital", "annual_mean_return", "annual_ret_std_dev",
                "annual_inflation", "annual_inf_std_dev", "monthly_withdrawals", "n_obs",
                "n_sim")

simulate_nav <- function(start_capital = 2000000, annual_mean_return = 5.0,
                         annual_ret_std_dev = 7.0, annual_inflation = 2.5,
                         annual_inf_std_dev = 1.5, monthly_withdrawals = 1000,
                         n_obs = 20, n_sim = 200) {
  #-------------------------------------
  # Inputs
  #-------------------------------------
  
  # Initial capital
  start.capital = start_capital
  
  # Investment
  annual.mean.return = annual_mean_return / 100
  annual.ret.std.dev = annual_ret_std_dev / 100
  
  # Inflation
  annual.inflation = annual_inflation / 100
  annual.inf.std.dev = annual_inf_std_dev / 100
  
  # Withdrawals
  monthly.withdrawals = monthly_withdrawals
  
  # Number of observations (in Years)
  n.obs = n_obs
  
  # Number of simulations
  n.sim = n_sim
  
  
  #-------------------------------------
  # Simulation
  #-------------------------------------
  
  # number of months to simulate
  n.obs = 12 * n.obs
  
  # monthly Investment and Inflation assumptions
  monthly.mean.return = annual.mean.return / 12
  monthly.ret.std.dev = annual.ret.std.dev / sqrt(12)
  
  monthly.inflation = annual.inflation / 12
  monthly.inf.std.dev = annual.inf.std.dev / sqrt(12)
  
  # simulate Returns
  monthly.invest.returns = matrix(0, n.obs, n.sim)
  monthly.inflation.returns = matrix(0, n.obs, n.sim)
  
  monthly.invest.returns[] = rnorm(n.obs * n.sim, mean = monthly.mean.return, sd = monthly.ret.std.dev)
  monthly.inflation.returns[] = rnorm(n.obs * n.sim, mean = monthly.inflation, sd = monthly.inf.std.dev)
  
  # simulate Withdrawals
  nav = matrix(start.capital, n.obs + 1, n.sim)
  for (j in 1:n.obs) {
    nav[j + 1, ] = nav[j, ] * (1 + monthly.invest.returns[j, ] - monthly.inflation.returns[j, ]) - monthly.withdrawals
  }
  
  # once nav is below 0 => run out of money
  nav[ nav < 0 ] = NA
  
  # convert to millions
  nav = nav / 1000000
  
  return(nav)
}

plot_nav <- function(nav) {
  
  layout(matrix(c(1,2,1,3),2,2))
  
  palette(c("black", "grey50", "grey30", "grey70", "#d9230f"))
  
  # plot all scenarios
  matplot(nav,
          type = 'l', lwd = 0.5, lty = 1, col = 1:5,
          xlab = 'Months', ylab = 'Millions',
          main = 'Projected Value of Initial Capital')
  
  # plot % of scenarios that are still paying
  p.alive = 1 - rowSums(is.na(nav)) / ncol(nav)
  
  plot(100 * p.alive, las = 1, xlab = 'Months', ylab = 'Percentage Paying',
       main = 'Percentage of Paying Scenarios', ylim=c(0,100))
  grid()
  
  
  last.period = nrow(nav)
  
  # plot distribution of final wealth
  final.nav = nav[last.period, ]
  final.nav = final.nav[!is.na(final.nav)]
  
  if(length(final.nav) ==  0) return()
  
  plot(density(final.nav, from=0, to=max(final.nav)), las = 1, xlab = 'Final Capital',
       main = paste0('Distribution of Final Capital\n', 100 * p.alive[last.period], '% are still paying'))
  grid()
}

# Define server logic required to generate and plot a random distribution
#
# Idea and original code by Pierre Chretien
# Small updates by Michael Kapler
#
server <- function(input, output, session) {
  
  getParams <- function(prefix) {
    input[[paste0(prefix, "_recalc")]]
    
    params <- lapply(paramNames, function(p) {
      input[[paste0(prefix, "_", p)]]
    })
    names(params) <- paramNames
    params
  }
  
  # Function that generates scenarios and computes NAV. The expression
  # is wrapped in a call to reactive to indicate that:
  #
  #  1) It is "reactive" and therefore should be automatically
  #     re-executed when inputs change
  #
  navA <- reactive(do.call(simulate_nav, getParams("a")))
  navB <- reactive(do.call(simulate_nav, getParams("b")))
  
  # Expression that plot NAV paths. The expression
  # is wrapped in a call to renderPlot to indicate that:
  #
  #  1) It is "reactive" and therefore should be automatically
  #     re-executed when inputs change
  #  2) Its output type is a plot
  #
  output$a_distPlot <- renderPlot({
    plot_nav(navA())
  })
  output$b_distPlot <- renderPlot({
    plot_nav(navB())
  })
  
}
# Run the application
shinyApp(ui = ui, server = server)

[andresrcs]

Could you try to follow this guide on debugging your shiny app, to narrow down your problem to the specific problematic part?

Shiny debugging and reprex guide

Shiny issues can be challenging to resolve relative to other problems with your code or statistical methods. Shiny apps are often large, complex projects with interacting files. When seeking help from others it is considered polite to: First, do your best to work through RStudio's debugging tools to diagnose your issue on your own. Often those shiny logs and tracebacks are useful to others trying to help out. Second, strive to minimize the effort required to replicate your issue. You can do this with a reproducible example ("reprex"). Shiny Debugging Errors in Shiny code can be difficult to track down. If you don't know where your problem is coming from, you can track it down with some o…

It's more likely that you get help if you provide a minimal reproducible example of your specific problem rather than the whole shiny app code.

[synchro]

ok sir, i will do what you advised me to do
thank you very much, my family

[synchro]

Hi my family

i just want to give you the feedback. fortunately the problem is solved. The code was correct, i just shut down mylapotop, and after that the shiny app is lunched with no problem.

Thank you very much