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computeExtrinsicNoiseKnownCor <- function (reporter1, reporter2, true.cor) {
# input: reporter1, reporter2: vectors of normalized reporter gene expression
# compute sample size
n <- length (reporter1)
# compute \sum C_i Y_i - n\bar{C}\bar{Y}
sum.cov <- sum (reporter1*reporter2) - n * mean (reporter1) * mean (reporter2)
# compute sample correlation
#sample.cor <- cor (reporter1, reporter2)
# unbiased estimator
unbiased <- sum.cov / (n-1)
# min MSE estimator
a <- 1/(true.cor^2) + (n-1)*(1+1/n)
min.mse <- sum.cov / a
# asymptotic estimator
asym <- sum.cov / n
# return a list of estimators
return (list (ELSS=asym, unbiased=unbiased, minMSE=min.mse, asymptotic=asym))
}
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