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- W4313593744 abstract "We propose a numerical method for obtaining exact confidence intervals of likelihood-based parameter estimators for general multi-parameter models. Although the test inversion method provides exact confidence intervals, it is applicable only to single-parameter models. Our new method can be applied to general multi-parameter models without loss of accuracy, which is in sharp contrast to other multi-parameter extensions of the test inversion. Using Monte Carlo simulations, we show that our method is feasible and provides correct coverage probabilities in finite samples." @default.
- W4313593744 created "2023-01-06" @default.
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- W4313593744 date "2023-09-01" @default.
- W4313593744 modified "2023-10-03" @default.
- W4313593744 title "A numerical method to obtain exact confidence intervals for likelihood-based parameter estimators" @default.
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- W4313593744 doi "https://doi.org/10.1016/j.jspi.2022.12.006" @default.
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