|Authors:||Shawn Mankad, George Michailidis, Moulinath Banerjee|
|Title:||Threshold Value Estimation Using Adaptive Two-Stage Plans in R|
|Abstract:||This paper introduces the R package twostageTE for estimation of an inverse regression function at a given point when one can sample an explanatory covariate at different values and measure the corresponding responses. The package implements a number of nonparametric methods for budget constrained threshold value estimation. Specifically, it contains methods for classical one-stage designs and also adaptive two-stage designs, which have been shown to yield more efficient and accurate results. A major advantage of the methods in package twostageTE is that threshold value estimation is performed without penalization or kernel smoothing, and hence, avoids the well-known problems of choosing the corresponding tuning parameter (regularization, bandwidth). The user can easily perform a two-stage analysis with twostageTE by (i) identifying the second stage sampling region from an initial sample, and (ii) computing various types of confidence intervals to ensure a robust analysis. The package twostageTE is illustrated through simulated examples.|
Page views:: 1079. Submitted: 2013-04-24. Published: 2015-10-07.
Threshold Value Estimation Using Adaptive Two-Stage Plans in R
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