g <- function(x) exp(-x)

MC.simple.est(g, 2, 4)

 [1] 0.1161926

> MC.simple.est <- function(g, a, b, n=1e4) {
+   xi <- runif(n,a,b)      # step 1
+   g.mean <- mean(g(xi))   # step 2
+   (b-a)*g.mean            # step 3
+ }
> g <- function(x) 1/log(x)
> 
> MC.simple.est(g, 2, 4)
[1] 1.922819
> integrate(g,2,4)
1.922421 with absolute error < 7.2e-14
>

peg.tab

peg.df

expand.gird()

> pag.tab <- matrix(c(762, 484, 327, 239, 468, 477), nrow=2)

> dimnames(pag.tab) <-list(Gender=c("Female","Male"),Party=c("Democrat","Independent","Republican"))

> pag.tab <- as.table(pag.tab)

> pag.tab

        Party

Gender   Democrat Independent Republican

  Female      762         327        468

  Male        484         239        477

> # Or

> pag.df <-expand.grid(Gender=c("Female","Male"),Party=c("Democrat","Independent","Republican"))

> pag.df

  Gender       Party

1 Female    Democrat

2   Male    Democrat

3 Female Independent

4   Male Independent

5 Female  Republican

6   Male  Republican

>

data(iris)

chernoff face

setosa

install.packages("aplpack")
library(aplpack)
data = iris
faces(data[1:25, c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")], 
    face.type = 1, scale = TRUE, labels = data$Species, plot.faces = TRUE, nrow.plot = 5, 
    ncol.plot = 5)

rm(list=ls())

mydata<-read.csv(file.choose())

mydata

fix(mydata)

install.packages("aplpack")

library(aplpack)

data =mydata

faces(data[1:30, c("Jamiyat", "M.R.S.J", "S.J.K", "M.SH","Masahat")], 

face.type = 1, scale = TRUE, 

labels = data$Species, 

plot.faces = TRUE, nrow.plot =6, 

ncol.plot = 5)

dgeom(X, prob = p)            
# p is the probability of success

dgeom(X, prob = p, log=TRUE)  
# log of the probability instead

dhyper(X, m, n, k)

dhyper(X, m, n, k, log = TRUE)