在绘制等高线图时，如何将条件添加到二元分布（x-mu=>；0）和（x-mu<；0）中？ bivariate.ESEP=0,1,0）+ （（t（mu-x）%*%solve（（I+eps）^2）%*%solve（Sigma）%*%k%*%（mu-x））

在绘制等高线图时，如何将条件添加到二元分布（x-mu=>；0）和（x-mu<；0）中？

bivariate.ESEP=0,1,0）+
（（t（mu-x）%*%solve（（I+eps）^2）%*%solve（Sigma）%*%k%*%（mu-x））^alp/2））*ifelse（x-mu）
bivariate.ESEP <- function(x, mu, Sigma ,eps) 
{
sqrt(det(k))/(2*(gamma(1+2/alp))*sqrt(det(Sigma)))*
exp(-(((t(x-mu)%*% solve((I-eps)^2)%*% solve(Sigma) %*%k%*%(x-mu))^alp/2)*ifelse(x-mu>=0,1,0) +
(((t(mu-x)%*% solve((I+eps)^2)%*% solve(Sigma)%*%k%*%(mu-x)))^alp/2)))*ifelse(x-mu<0,1,0)
}

mu <- c(179.81,22.2)
Sigma <- matrix(c(0.6,0.35,0.35,2), nrow=2)

Sigma<-Sigma1
eps<-matrix(c(-0.186,0,0,0.6), nrow=2)
k<-matrix(c(1,0,0,1), nrow=2)
I<-matrix(c(1,0,0,1), nrow=2)
alp =1
x1 <- seq(150, 220)
x2 <- seq(0, 40)
z <- outer(x1, x2, FUN=function(x1, x2, ... ){
         apply(cbind(x1,x2), 1, bivariate.ESEP, ...)
       }, mu=mu, Sigma=Sigma ,eps = eps)
plot(dat1, xlab="Ht", ylab="BMI", pch=19, cex=.7)
contour(x1, x2, z, col="blue", drawlabels=FALSE, nlevels= 20,
    xlab=expression(x[1]), ylab=expression(x[2]), lwd=1, add = TRUE)