T distribution #1
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app t-dist, replicate from z_dist
| # min = 1, max = 200, value = 1, step = 1 | ||
| # ) | ||
| ), | ||
| div(# critical values readout |
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added critical values readout back in - how this should look/feel/act is still up for debate
| output$critical_values <- renderPrint({ | ||
| tagList( | ||
| tags$label("Critical values"), | ||
| withMathJax(), | ||
| labels() %>% pull(t, df) %>% label_p_value_html() %>% map(p) | ||
| labels() %>% select(t, df) %>% purrr::pmap(label_p_value_html) %>% map(p) |
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pt takes two inputs, need a different approach (purrr:pmap maps over df rows)
| outputOptions(output, "mode", suspendWhenHidden = FALSE) | ||
| outputOptions(output, "help", suspendWhenHidden = FALSE) | ||
| } | ||
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| shiny::shinyApp(ui, server) | ||
| shiny::shinyApp(ui, server) %>% shiny::runApp() |
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added for non-interactive use (as the file name is non-standard, and doesn't trigger Rstudio black magic integrations
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| library(shiny) | |||
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so I actually forgot to push the progress I already made on the t-distribution app. Sorry!
R/t-distribution
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| # App: t_distribution | |||
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filename should be app.R for shiny and Rstudio integrations to work. .R extension is also nice...
R/t-distribution
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| STARTING_DF <- 2 | ||
| STARTING_P_VALUE <- | ||
| pt(STARTING_T_VALUE / 2, STARTING_DF, lower.tail = STARTING_T_VALUE <= 0) %>% round(3) | ||
| RANGE <- c(-4, 4) # range for T value |
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We'll need to add dynamic range, as with low df the critical values fall outside of the -4, 4 range.
min/max(range, actual) in the render should do the trick
R/t-distribution
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| class = "d-flex", | ||
| sliderInput("alpha", "Type I error, \\(\\alpha\\)", 0.01, 0.2, 0.05, 0.01) | ||
| ), | ||
| div(# degree of freedom |
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df is required in all modes, it also affects p-values, move outside of conditional panel
R/t-distribution
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| crit_lower <- reactive(qt(input$alpha / 2, input$df)) # find lower critical value | ||
| crit_upper <- reactive(qt(1 - input$alpha / 2, input$df)) # find upper critical value | ||
| data <- reactive(tibble( | ||
| t = c( |
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re; adaptive range, check if critical t falues fall outside of range, and if necessary, extend the range
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we'll need to see if that has implications for the precision, as for df=1 the range is ~-25,25 or so
R/t-distribution
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| updateNumericInput(session, "t_value", value = tValue()) | ||
| }) %>% bindEvent(input$p_to_t) | ||
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| output$critical_values <- renderPrint({ |
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note that this was unused, but also defective (can't pull 2 variables into a function like that, the function sees it as one variable.)
See update in my patch, and purrr:pmap
R/t-distribution
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| ## PLOT --------------------------------------------------------- | ||
| output$distribution <- renderPlot({ | ||
| plot <- data() %>% ggplot(aes(t, d)) |
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note that the y scale depends on the degrees of freedom. We may want to fix the scale to 0,0.4 (ish, whatever is reasonable for df=\Inf), so that changes in y scale are more obvious to see.
- Fixed y-axis to show changes across df - Modified dynamically extend plot range for low df - Add check box to show normal distribution - Fixed error not showing df in p_values mode - Fixed typo error: label_t_value => label_p_value
- Modified dynamically extend plot range for low df - Add check box to show normal distribution - Fixed error not showing df in p_values mode - Fixed typo error: label_t_value => label_p_value
Update display mode
…in previous versions, display breaks for t-values
…version, display breaks for z-values.
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