R: Log density of bivariate Gaussian distribution with symmetric...

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 1.2 Index]