cor.me.matrix: A function to calculate measurement error estimates for all...

In MeasurementError.cor: Measurement Error model estimate for correlation coefficient

Description

Given a matrix ( p x n) for observed values of p variables and a corresponding matrix for their standard errors, the all pairwise measurement error estimates for true correlations are returned

Usage

cor.me.matrix(exp, se)

Arguments

exp	observed value marix
se	standard error matrix

Value

The final estimates for true correlation (i.e. cor.true) from the measurement error model

Note

The function involves using quasi-newton for linear optimization, "BFGS" is the only implemented method now. Refer to cor.me.vector for more details.

Author(s)

Beiying Ding

References

Ding, B.Y. and Gentleman, R.(2003) Measurement error model for correlation coeffcient estimation and its application in microarray analsysis

See Also

cor.me.vector

Examples

 exp <- matrix(abs(rnorm(200,1000,20)),ncol=10)
 se <- matrix(abs(rnorm(200,50,5)),ncol=10)
 cor.me.matrix(exp,se)

MeasurementError.cor documentation built on Nov. 8, 2020, 5:08 p.m.