m1bgumbel: Bimodal Gumbel: Theoretical E(X)

Description Usage Arguments Value Examples

View source: R/m1bgumbel.R

Description

Bimodal Gumbel: Theoretical E(X)

Usage

1
m1bgumbel(mu, sigma, delta)

Arguments

mu

First location parameter.

sigma

Scale parameter.

delta

Second location parameter.

Value

Vector.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
(EX <- m1bgumbel(mu = -2, sigma = 1, delta = -1))


# Comparison: Theoretical E(X) and empirical mean

x <- rbgumbel(100000, mu = -2, sigma = 1, delta = -1)
mean(x)
abs(EX - mean(x))/abs(EX) # relative error

# grid 1

mu <- seq(-5, 5, length.out = 100)
delta <- seq(-5, 5, length.out = 100)
z <- outer(
  X <- mu,
  Y <- delta,
  FUN = function(x, y) m1bgumbel(mu = x, sigma = 1, delta = y)
)

persp(x = mu, y = delta, z = z, theta = -60, ticktype = 'detailed')

# grid 2

mu <- seq(-5, 5, length.out = 100)
delta <- seq(-5, 5, length.out = 100)
sigmas <- seq(.1, 10, length.out = 20)

for (sigma in sigmas) {
 z <- outer(
   X <- mu,
   Y <- delta,
    FUN = function(x, y) m1bgumbel(mu = x, sigma = sigma, delta = y)
 )
 persp(x = mu, y = delta, z = z, theta = -60, zlab = 'E(X)')
 Sys.sleep(.5)
}

bgumbel documentation built on April 1, 2021, 1:06 a.m.