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| library(shiny) | |
| source('var.test.R') | |
| shinyServer(function(input,output,session){ | |
| observe({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, | |
| sep=input$sep) | |
| updateSelectInput(session, "variable", choices=names(dt)) | |
| }) | |
| output$statistic <- renderTable({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, | |
| sep=input$sep) | |
| y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable | |
| res <- data.frame(Min=min(y), Var=var(y), | |
| Max=max(y), n=length(y)) | |
| colnames(res) <- c('Mínimo', 'Varianza', 'Máximo', 'Número obs') | |
| res | |
| }, align='c', bordered=TRUE) | |
| output$appPlot <- renderPlot({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, sep=input$sep) | |
| par(mfrow=c(1, 2), bg='gray98') | |
| y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable | |
| hist(y, col='deepskyblue3', freq=F, las=1, | |
| xlab=as.character(input$variable), | |
| main='Histograma y densidad', ylab='Densidad') | |
| lines(density(y), lwd=4, col='firebrick3') | |
| qqnorm(y, las=1, main='QQplot', | |
| pch=19, col='deepskyblue3', | |
| ylab=as.character(input$variable)) | |
| qqline(y) | |
| ks <- ks.test(x=y, y=pnorm) | |
| legend('topleft', bty='n', col='red', text.col='deepskyblue3', | |
| legend=paste('Valor P=', round(ks$p.value,2))) | |
| }) | |
| output$inputData <- renderTable({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, | |
| sep=input$sep) | |
| dt | |
| }) | |
| output$resul1 <- renderText({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, | |
| sep=input$sep) | |
| y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable | |
| ph <- var.test(x=y, alternative=input$h0, | |
| null.value=input$sigma20, | |
| conf.level=input$alfa) | |
| paste0('El estadístico de prueba es ', round(ph$statistic, 2), | |
| ' con un valor-P de ', round(ph$p.value, 4), '.') | |
| }) | |
| output$resul2 <- renderText({ | |
| inFile <- input$file1 | |
| if(is.null(inFile)) | |
| dt <- read.table('var_data.txt', header=T, sep='\t') | |
| else dt <- read.csv(inFile$datapath, header=input$header, | |
| sep=input$sep) | |
| y <- na.omit(dt[, input$variable]) # Para sacar los NA de la variable | |
| ph <- var.test(x=y, alternative=input$h0, | |
| null.value=input$sigma20, | |
| conf.level=input$alfa) | |
| intervalo <- paste("(", round(ph$conf.int[1], digits=4), ", ", | |
| round(ph$conf.int[2], digits=4), ").", sep='') | |
| paste0('El intervalo de confianza del ', 100*input$alfa, | |
| '% para la varianza poblacional es ', intervalo) | |
| }) | |
| output$miteoria <- renderUI({ | |
| HTML(markdown::markdownToHTML(knit(input='include.md', quiet=TRUE))) | |
| }) | |
| }) | |