# censCor: Correlation In USGS-R/smwrQW: Tools for censored data analysis

## Description

Computes the maximum likelihood estimate of the correlation between two possibly left-censored vectors. It is equivalent the the Pearson product-moment correlation for uncensored data.

## Usage

 `1` ```censCor(x, y, Full = TRUE, na.rm = TRUE) ```

## Arguments

 `x` any data that can be converted to a left-censored data object. `y` any data that can be converted to a left-censored data object. `Full` how to compute the mean and standard deviation of `x` and `y`. See Details. `na.rm` logical, remove missing values before computing the correlation?

## Details

`Full` may be either logical or a numeric vector. If `Full` is `TRUE`, then estimate the means and standard deviations for `x` and `y`. If `Full` is `FALSE`, use the initial maximum likelihood estimate for those statistics. Otherwise `Full` can be a named vector containing `mnx`, the mean for `x`; `sdx`, the standard deviation for `x`; `mny`, the mean for `y`; `sdy`, the standard deviation for `y`. `Full` can be set to `FALSE` if the optimization fails at large censoring levels or to improve processing speed for large sample sizes.

## Value

A vector with these names:

 `cor` the correlation between `x` and `y`. `mnx` the mean of `x`. `sdx` the standard deviation of `x`. `mny` the mean of `y`. `sdy` the standard deviation of `y`. `cx` the proportion of censored values of `x`. `cy` the proportion of censored values of `y`. `cxy` the proportion of censored values common to `x` and `y`. `n` the number of observations. `ll0` the log likelihood for cor=0 `llcor` the log likelihood for cor=cor

## References

Lyles, R.H., Williams, J.K., and Chuachoowong R., 2001, Correlating two viral load assays with known detection limits: Biometrics, v. 57 no. 4, p. 1238–1244.

## Examples

 ```1 2 3 4 5 6 7 8``` ```# Simple no censoring set.seed(450) tmp.X <- rnorm(25) tmp.Y <- tmp.X/2 + rnorm(25) cor(tmp.X, tmp.Y) censCor(tmp.X, tmp.Y) # Some censoring censCor(as.lcens(tmp.X, -1), as.lcens(tmp.Y, -1)) ```

USGS-R/smwrQW documentation built on Sept. 22, 2018, 4:35 a.m.