Storge changes

lecture/Exercise/.Rhistory

@@ -0,0 +1 @@
+q()

lecture/Exercise/exercise.r

@@ -0,0 +1,25 @@
+# Setzen des Pfades und Einlesen der Daten
+library(httpgd)
+hgd(port = getOption("httpgd.port", 11111),
+    token = getOption("httpgd.token", FALSE),)
+
+setwd("/config/workspace/assistenz-r/lecture")
+Daten <- read.csv("Mietspiegel.csv",header=TRUE,sep=";",fill=TRUE)
+
+Daten[,"bad"] <- as.factor(Daten[,"bad"])
+Daten[,"kueche"] <- as.factor(Daten[,"kueche"])
+Daten[,"lage"] <- as.factor(Daten[,"lage"])
+Daten[,"zh"] <- as.factor(Daten[,"zh"])
+
+# Berechnung der linearen Regression
+
+model <- lm( mieteqm ~ flaeche + bjahr + bad + kueche + lage + zh, data=Daten)
+
+plot(model)
+
+y <- Daten[,"mieteqm"] 
+Prognosen <- model$fitted.values 
+Prognosefehler <- mean( abs( y - Prognosen ) )
+Prognosefehler
+
+Sys.sleep(10000)

project/App-Kredit/app.r

@@ -0,0 +1,50 @@
+
+
+
+################
+# Im folgenden Abschnitt wird das User Interface (UI) definiert
+ui <- fluidPage(
+
+  # Titel der App
+  titlePanel("Kredit"),
+
+  # Layout für die Eingaben in die App und die Ausgaben
+  sidebarLayout(
+
+    # Die Definition der Eingabefelder auf der linken Seite
+    sidebarPanel(
+      sliderInput("obs", 
+                  "Number of observations:", 
+                  min = 1, 
+                  max = 1000, 
+                  value = 500),
+      selectInput("select", h3("status"), 
+                  choices = list("no checking account" = 1, "... < 0 DM" = 2,
+                                 "0<= ... < 200 DM" = 3, "... >= 200 DM / salary for at least 1 year" = 4 ), selected = 1),
+      selectInput("select", h3("credit_history"), 
+                  choices = list("delay in paying off in the past" = 0, "critical account/other credits elsewhere" = 1,
+                                 "no credits taken/all credits paid back duly" = 2, "existing credits paid back duly till now" = 3,
+                                 "all credits at this bank paid back duly" = 4), selected = 0),
+      selectInput("select", h3("purpose"), 
+                  choices = list("others" = 0, "car (new)" = 1, "car (used)" = 2, "furniture/equipment" = 3, "radio/television" = 4,
+                                 "domestic appliances" = 5, "repairs" = 6, "education" = 7, "vacation" = 8, "retraining" = 9,
+                                 "business" = 10), selected = 0),
+    ),
+    # der Hauptbereich der Nutzeroberfläche für die Ausgabe der Ergebnisse
+    mainPanel(
+      plotOutput("distPlot")
+    )
+  )
+)
+
+############
+
+
+server <- function(input, output) {
+  output$distPlot <- renderPlot({
+    # generate an rnorm distribution and plot it
+    dist <- rnorm(input$obs)
+    hist(dist)
+  })
+}
+shinyApp(ui = ui, server = server)

project/read_SouthGermanCredit.R

@@ -3,7 +3,7 @@ dat <- read.table("SouthGermanCredit.asc", header=TRUE)
 
 ## dat contains numbers for all variables.
 
-## variables duration, amount and age are truly quantitative
+## variables durtion, amount and age are truly quantitative
 ## variables installment_rate, present_residence and number_credits are
     ### quantitative in the data, but are in fact discretized scores for 
     ### an underlying quantitative variable

project/run-Kredit.r

@@ -0,0 +1,4 @@
+  setwd("/config/workspace/assistenz-r/project")
+  library(shiny)
+
+  runApp("App-Kredit",port = 12345)