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

In idr: Irreproducible Discovery Rate

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).

Author(s)

Qunhua Li

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

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

idr documentation built on June 21, 2022, 9:05 a.m.