Using the result, we may better construct a confidence region for the parameter β.
Following standard regression theory, we can construct a confidence interval for this prediction as (3).
After the AMA values are obtained for each bootstrap sample, this set can be used to construct a confidence interval.
Based on a standard heuristic algorithm for it, we present a method to construct a confidence neighborhood for a computed solution.
Inspired by this idea, we use the reconstructed video sequence ( widehat{mathbf{X}} ) to construct a confidence map denoted as O = [o 1, o 2 …, o T ], where the element of O is 0 or 1.
In this paper, we develop a method to construct a confidence interval for V by analysing the variability produced by each level of sampling (i.e., between and within sections' variability).
Based on Theorem 2.3, (hat{l}_{mathrm{ad}}(beta)) can be used to construct a confidence region for β, hat{I}_{mathrm{ad}} tilde{beta})=bigl{ tilde{beta}:hat{l}_{mathrm{ad}}( beta)leq c_{alpha}bigr}, where (P chi^{2}_{p}leq c_{alpha})=1-alpha), and (P{betainhat {I}_{mathrm{ad}} tilde{beta})}=1-alpha+o(1)).
Next, we present some basic sample size formulas for when we plan to collect a sample of either continuous or binary data and then wish to construct a confidence interval for the population mean or the population proportion with a certain degree of precision.
We construct a confidence interval by the profile likelihood method.
By the delta method it is possible to construct a confidence band for the SROC curve, as explained above.
For testing statistical significance of differences an alternative procedure is to construct a confidence interval for the difference, and observe whether this includes the value zero.
