d.binormal {idr} | R Documentation |
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
[Package idr version 1.3 Index]