#' @title Simulacion Variable Aleatoria Normal Bivariada via Box Muller
#' @description Genera valores aleatorios simulados que siguen una distribucion Normal con
#' media cero y varianza uno aplicando el metodo de Box-Muller.
#' @param n Numero de valores aleatorios a generar.
#' @examples
#' snormalBM(100)
#' snormalBM(200)
#' @references Ross, S.M. (1999) Simulacion. Prentice Hall
#' @export
snormalBM<-function(n)
{
x<-rep(0,n)
y<-rep(0,n)
j<-0
while(j<=n)
{
u<-rep(0,2)
u[1]<-stats::runif(1)
u[2]<-stats::runif(1)
x[j]<-sqrt(-2*log(u[1]))*cos(2*pi*u[2])
y[j]<-sqrt(-2*log(u[1]))*sin(2*pi*u[2])
j<-j+1
}
print(c("valores generados de X"))
print(x)
print(c("valores generados de Y"))
print(y)
x<-sort(x)
y<-sort(y)
f<-function(x,y){p<-(1/2*pi)*exp(-(1/2)*((x^2)+(y^2)))}
z<-outer(x,y,f)
graphics::persp(x, y, z, theta = 40, phi = 40, expand = 0.5, col ="deepskyblue3" ,
border="deepskyblue4",
ltheta = 100, shade = 0.80, ticktype = "detailed",
xlab = "x", ylab = "Y", zlab = "z",
main="Grafico de Perspectiva")
}
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