#' @title Simulacion Variable Aleatoria Normal Bivariada via Coordenadas Polares
#' @description Genera valores aleatorios simulados que siguen una distribucion Normal con
#' media cero y varianza uno aplicando el metodo de Coordenadas Polares.
#' @param n Numero de valores aleatorios a generar.
#' @examples
#' snormalCP(100)
#' snormalCP(50)
#' @references Ross, S.M. (1999) Simulacion. Prentice Hall.
#' @export
#'
snormalCP<-function(n)
{
x<-rep(0,n)
y<-rep(0,n)
j<-1
while(j<=n)
{
u<-rep(0,2)
u[1]<-stats::runif(1)
u[2]<-stats::runif(1)
v1<- 2*u[1]-1
v2<-2*u[2]-1
s <-v1^2 + v2^2
while(s>1)
{u<-rep(0,2)
u[1]<-stats::runif(1)
u[2]<-stats::runif(1)
v1<- 2*u[1]-1
v2<-2*u[2]-1
s <-v1^2 + v2^2
}
xx<- sqrt((-2*log(s))/s)*v1
yy<- sqrt((-2*log(s))/s)*v2
x[j]<-xx
y[j]<-yy
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 ="mediumpurple2",border="mediumpurple3",
ltheta = 100, shade = 0.80, ticktype = "detailed",
xlab = "x", ylab = "Y", zlab = "z", main="Grafico de Perspectiva")
}
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