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- W4386439677 abstract "This chapter displays M-statistics in action: the maximum concentration (MC) and mode exact statistical inference are applied to major statistical parameters. It develop the MC estimator of the heterogeneity variance in the meta-analysis model on the log scale. The chapter also develops a novel estimator, confidence interval (CI), and hypothesis test for the Poisson rate using methods of M-statistics. It also derives optimal statistical inference for normal standard deviation. The chapter employs M-statistics to derive the exact optimal CI and hypothesis testing for the simplest and yet fundamental one-parameter Pareto distribution. It presents exact unbiased statistical inference for the coefficient of variation (CV) for the lognormal distribution. The chapter illustrates the M-statistics by developing the exact statistical inference for the effect size and its reciprocal, CV. Estimation of binomial probability from iid Bernoulli experiments is one of the oldest statistical problems." @default.
- W4386439677 created "2023-09-06" @default.
- W4386439677 date "2023-09-05" @default.
- W4386439677 modified "2023-10-01" @default.
- W4386439677 title "M‐statistics for major statistical parameters" @default.
- W4386439677 doi "https://doi.org/10.1002/9781119891826.ch5" @default.
- W4386439677 hasPublicationYear "2023" @default.
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