Recovering Fisher-Information from the MGF Alone without Requiring Explicit PMF or PDF from a One-Parameter Exponential Family

N. Mukhopadhyay
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Abstract

It is well-known that a finite moment generating function (m.g.f.) corresponds to a unique probability distribution. So, an important question arises: Is it possible to obtain an expression of Fisher-information, IX(Ɵ); using the m.g.f. alone, that is without requiring explicitly a probability mass function (p.m.f.) or probability density function (p.d.f.), given that the p.m.f. or p.d.f came from a one-parameter exponential family? We revisit the core of statistical inference by developing a clear link (Theorem 1.1) between the m.g.f. and IX(Ɵ). Illustrations are included.
在单参数指数族中不需要显式PMF或PDF的情况下,从MGF中单独恢复fisher信息
众所周知,有限矩生成函数(m.g.f.)对应于唯一的概率分布。因此,一个重要的问题出现了:是否可能获得Fisher信息的表达式IX(Ɵ);单独使用m.g.f,即不需要明确的概率质量函数(p.m.f.)或概率密度函数(p.d.f.),假设p.m.f.或p.d.f来自一个单参数指数族?我们通过在m.g.f.和IX(Ɵ)之间建立明确的联系(定理1.1)来重新审视统计推断的核心。包括插图。
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