Frequentist inference, Bernoulli model

{r, echo=FALSE}
inputPanel(
  sliderInput("p", label = "Probability (true)",
              min = 0, max = 1, value = 0.3, step = 0.05),
  sliderInput("n", label = "Sample size",
              min = 10, max = 1000, value = 10, step = 10),
  sliderInput("seed", label = "Random seed",
              min = 0, max = 100, value = 0, step = 10)
)
renderPlot({
    par(las = 1)
    set.seed(input$seed)
    y <- rbinom(n = 1000, size = 1, p = input$p)
    pt <- seq(0, 1, by = 0.0005)
    L <- sapply(pt, function(z) 
        prod(dbinom(y[1:input$n], size = 1, prob = z)))
    plot(pt, L, type = "l", col="#3498db",
        ylab = "Likelihood", xlab="p",
        sub=paste0("Mean = ", round(mean(y[1:input$n]), 2), " (", 
            sum(1-y[1:input$n]), " 0s & ", sum(y[1:input$n]), " 1s)"),
        main = paste("Estimate =", round(pt[which.max(L)], 2)))
    abline(v = input$p, lwd = 2, col = "#c7254e")
    abline(v = pt[which.max(L)], lwd = 2, col = "#18bc9c")
})