inst/apps/distribution_geng_functions/server.R

server = function(input, output, session) {
  
t <- reactive({ signif(seq(min(input$range.geng), max(input$range.geng), length = 500), digits = 4)})
p <- signif(seq(0, 1, length = 500), digits = 4) 
C <- reactive({ pgeng(t(), input$theta.geng, input$beta.geng, input$kappa.geng)})
P <- reactive({ dgeng(t(), input$theta.geng, input$beta.geng, input$kappa.geng)})
R <- reactive({ 1-C()})
h <- reactive({ exp(log(P())-log(R()))})
H <- reactive({ -1*log(1-pgeng(t(), input$theta.geng, input$beta.geng, input$kappa.geng))})
Q <- reactive({ qgeng(p, input$theta.geng, input$beta.geng, input$kappa.geng)})
df <- reactive({data.frame(Time = t(),PROB = p, CDF = C(),PDF = P(),REL = R(),haz = h(),HAZ = H(), QUANT = Q())})

  output$gengC <- renderMetricsgraphics({
  mjs_plot(df(), x = Time, y = CDF, decimals = 4, top = 0) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Time (t)', y_label = 'F(t)')%>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")}) 
  
  output$gengP <- renderMetricsgraphics({
  mjs_plot(df(), x = Time, y = PDF, decimals = 4) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Time (t)', y_label = 'f(t)') %>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")})
  
  output$gengR <- renderMetricsgraphics({
  mjs_plot(df(), x = Time, y = REL, decimals = 4) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Time (t)', y_label = 'S(t)') %>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")})
  
  output$gengh <- renderMetricsgraphics({
  mjs_plot(df(), x = Time, y = haz, decimals = 4) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Time (t)', y_label = 'h(t)') %>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")})
  
  output$gengH <- renderMetricsgraphics({
  mjs_plot(df(), x = Time, y = HAZ, decimals = 4) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Time (t)', y_label = 'H(t)') %>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")})
  
  output$gengQ <- renderMetricsgraphics({
  mjs_plot(df(), x = PROB, y = QUANT, decimals = 4) %>%
  mjs_line(area = TRUE) %>%
  mjs_labs(x_label = 'Probability', y_label = 'q(t)') %>%
  mjs_add_css_rule("{{ID}} .mg-active-datapoint { font-size: 20pt }")})
}

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teachingApps documentation built on July 1, 2020, 5:58 p.m.