\[ X{\sim}exp(\lambda) \]
Nota: Distribución que modela los tiempos de espera entre sucesos que siguen una distribución de Poisson.
\[ P(X=x)=\lambda\exp{\left\{-\lambda{\cdot}x\right\}}\text{ con }0{\leq}X{\leq}\infty \text{ y }\lambda>0 \]
\[ P(X=x)=\frac{1}{\lambda}\exp{\left\{-\frac{1}{\lambda}{\cdot}x\right\}}\text{ con }0{\leq}X{\leq}\infty \text{ y }\lambda>0 \]
\[ E(X)=\frac{1}{\lambda} \]
\[ Var(X)=\frac{1}{\lambda^2} \]
library(ggfortify)
## Loading required package: ggplot2
Nota: \(rate=\frac{1}{\lambda}\)
exponencial <- function(rate,fill=NULL,colour=NULL,p=NULL){
ggdistribution(func=dexp,
x=seq(from=0,
to=3,
by=0.1),
rate=rate,
fill=fill,
colour=colour,
p=p)
}
exponencial(rate=1,fill="gray",colour="black",
p=exponencial(rate=3,fill="red",colour="yellow",
p=exponencial(rate=5,fill="blue",colour="green")))
densidad.exponencial <- function(x,rate){
ggdistribution(dexp,
seq(0, +3, 0.1),
rate=rate,
colour = "blue",
p = ggdistribution(dexp,
seq(x-0.05, x+0.05, 0.1),
rate=rate,
colour ="blue",
fill = "blue"))
}
densidad.exponencial(x=1,rate=3)
dexp(x=1,rate=3)
## [1] 0.1493612
distribucion.exponencial <- function(q,rate){
ggdistribution(dexp,
seq(0, +3, 0.1),
rate=rate,
colour = "blue",
p = ggdistribution(dexp,
seq(0, q, 0.1),
rate=rate,
colour ="blue",
fill = "blue"))
}
distribucion.exponencial(q=1,rate=3)
pexp(q=1,rate=3)
## [1] 0.9502129
probabilidad.exponencial <- function(a,b,rate){
ggdistribution(dexp,
seq(0, 3, 0.1),
rate = rate,
colour = "blue",
p = ggdistribution(dexp,
seq(a, b, 0.1),
rate = rate,
colour ="blue",
fill = "blue"))
}
probabilidad.exponencial(a=0.5,b=1,rate=3)
\[ P(a{\leq}T{\leq}b)=P(T{\leq}b)-P(T{\leq}a) \]
pexp(q=1,rate=3)-pexp(q=0.5,rate=3)
## [1] 0.1733431
pexp(q=0.5,rate=3)-pexp(q=0.25,rate=3)
## [1] 0.2492364
\(P_{exp\left(\frac{1}{3}\right)}(0.125{\leq}X{\leq}0.25)\)
\(P_{exp\left(\frac{1}{3}\right)}(0.125{\leq}X{\leq}0.675)\)
\(P_{exp\left(\frac{1}{3}\right)}(0.975{\leq}X{\leq}1)\)