idr (version 1.3)

d.binormal: Log density of bivariate Gaussian distribution with symmetric marginals

Description

Compute the log-density for parameterized bivariate Gaussian distribution N(mu, mu, sigma, sigma, rho).

Usage

d.binormal(z.1, z.2, mu, sigma, rho)

Arguments

z.1

a numerical data vector on coordinate 1.

z.2

a numerical data vector on coordinate 1.

mu

mean

sigma

standard deviation

rho

correlation coefficient

Value

Log density of bivariate Gaussian distribution N(mu, mu, sigma, sigma, rho).

References

Q. Li, J. B. Brown, H. Huang and P. J. Bickel. (2011) Measuring reproducibility of high-throughput experiments. Annals of Applied Statistics, Vol. 5, No. 3, 1752-1779.

Examples

# NOT RUN {
z.1 <- rnorm(500, 3, 1)
rho <- 0.8

## The component with higher values is correlated with correlation coefficient=0.8 
z.2 <- rnorm(500, 3 + 0.8*(z.1-3), (1-rho^2))
mu <- 3
sigma <- 1
den.z <- d.binormal(z.1, z.2, mu, sigma, rho)

den.z
# }