Description Usage Arguments Details Value Author(s) Examples
Uses isotonic regression and PAVA to form a point estimate.
1 | threshold_estimate_ir(explanatory, response, Y_0)
|
explanatory |
Explanatory sample points |
response |
Observed responses at the explanatory sample points |
Y_0 |
Threshold of interest |
This is an internal function not meant to be called directly. It function relies on the PAVA algorithm to form a point estimate.
list(threshold_estimate_explanatory = estim_x, threshold_estimate_response = fit$y[ind], threshold = Y_0, Y_hat = fit$y, index = ind)
threshold_estimate_explanatory |
Point estimate of d_0 |
threshold_estimate_response |
Estimate of f(d_0), which may not be exactly equal to the desired threshold |
threshold |
Threshold of interest (equal to Y_0 input) |
Y_hat |
Fitted values from PAVA |
index |
index that corresponds to the point estimate, so that Y_hat[index]=threshold_estimate_response |
Shawn Mankad
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | X=runif(25, 0,1)
Y=X^2+rnorm(n=length(X), sd=0.1)
stageOneAnalysis(X, Y, 0.25, type="IR-wald", 0.99)
## The function is currently defined as
function (explanatory, response, Y_0)
{
n = length(response)
if (sum(response < Y_0) == n) {
warning("Y_0 is outside observed region")
list(threshold_estimate_explanatory = max(explanatory),
threshold_estimate_response = max(response), threshold = Y_0,
Y_hat = max(response), index = n)
}
else if (sum(response >= Y_0) == n) {
warning("Y_0 is outside observed region")
list(threshold_estimate_explanatory = min(explanatory),
threshold_estimate_response = min(response), threshold = Y_0,
Y_hat = min(response), index = 1)
}
else {
fit = pava(explanatory, response)
if (sum(fit$y >= Y_0) == 0) {
warning("estimate is on the boundary")
ind = n
estim_x = fit$x[ind]
}
else if (sum(fit$y <= Y_0) == 0) {
warning("estimate is on the boundary")
ind = min(which(fit$y >= Y_0))
estim_x = fit$x[ind]
}
else {
ind = min(which(fit$y >= Y_0))
estim_x = fit$x[ind]
}
list(threshold_estimate_explanatory = estim_x,
threshold_estimate_response = fit$y[ind],
threshold = Y_0, Y_hat = fit$y, index = ind)
}
}
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