asudipta

library(shiny)
library(datasets)

# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {

  # Return the requested dataset
  datasetInput <- reactive({
    switch(input$dataset,
           "rock" = rock,

asudipta

library(shiny)
 
shinyServer(function(input, output) {
  
  TechSkills <- c( "Ipython", "Shiny R", "Matlab/Octave", "VBA", "Hadoop/MapReduce", "Apache Spark")

TS_ACC <-c(25,26,22,12,22,27)
TS_AUR <- c(8,6,7,5,4,7)
TS_QUIN <- c(12,12,14,24,17,27)
ACCENTURE=data.frame(TechSkills, TS_ACC)

asudipta

hair_eye_male <- subset(as.data.frame(HairEyeColor), Sex == "Male")
n2 <- nPlot(Freq ~ Hair, group = 'Eye', data = hair_eye_male, type = 'multiBarChart')
n2

asudipta

# Specifying functions:

CalcResiduals <- function(th, data) {
   # Calculates the e_t and h_t for the GARCH(1, 1) model with given parameters.
   #
   # Argumentss:
   #   th: Parameters
   #          th[1] -> mean
   #          th[2] -> alpha.0
   #          th[3] -> alpha.1