amp (version 1.0.0)

ic.pearson: Pearson Correlation IC and estimate

Description

This function takes a set of observations, and returns an estimate and its corresponding estimated IC matrix for the estimates of the pearson correlation. Estimates of the covariance are generated using the empirical influence function. The first column of your data should correspond to the variable of interest (the variable for which pearson correlation is calculated).

Usage

ic.pearson(observ, what = "both", control = NULL)

Arguments

observ

the observed data. The first column should be the outcome.

what

the desired return value. Should be one of "ic" (influence curve), "est" (estimate), or "both".

control

any other control parameters to be passed to the estimator.

Value

If what is:

- "est", then return the estimated person correlation.

- "ic", then return the estimated IC of the person correlation estimate.

- "both", then return both the estimated pearson correlation and the estimated IC of the person correlation estimate.

Examples

# NOT RUN {
dat <- matrix(rnorm(80), nrow = 20)
ic.pearson(dat, what = "both")
## Note that the estimate is the same as what is found using \code{cor}
cor(dat)[1, ]

# }