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Bartlett identities and large deviations in likelihood theory

机译:Bartlett身份和似然理论中的大偏差

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The connection between large and small deviation results for the signed square root statistic R is studied, both for likelihoods and for likelihood-like criterion functions. We show that if p-1 Barlett identities are satisfied to first order, but the pth identity is violated to this order, then cum_q(R)=O(n~(-q/2)) for 3<=q, whereas cum_p(R)=k_pn~(-(p-2)/2)+O(n~(-p/2)). We also show that the large deviation behavior of R is determined by the values of p and k_p. The latter result is also valid for more general statistics. Affine (additive and/or multiplicative) correction to R and R~2 are special cases corresponding to p=3 and 4. The cumulant behavior of R gives a way of characterizing the extent to which R-statistics derived from criterion functions other than log likelihoods can be expected to behave like ones derived from true log likelihoods, by looking at the number of Bartlett identities that are satisfied. Empirical and nonparametric survival analysis type likelihoods are analyzed from this perspective via the device of "dual criterion functions."
机译:对于似然和似然准则函数,研究了有符号平方根统计量R的大偏差结果和小偏差结果之间的联系。我们证明,如果p-1 Barlett身份满足一阶,但pth身份违反了该顺序,则cum_q(R)= O(n〜(-q / 2))对于3 <= q ,而cum_p(R)= k_pn〜(-(p-2)/ 2)+ O(n〜(-p / 2))。我们还表明,R的大偏差行为由p和k_p的值确定。后一结果对于更一般的统计数据也是有效的。对R和R〜2的仿射(加和/或乘)校正是对应于p = 3和4的特殊情况。R的累积行为提供了一种方法,用于表征从对数以外的标准函数导出的R统计量的程度通过查看满足的Bartlett身份,可以预期似然行为的行为类似于从真实对数似然得出的行为。经验和非参数生存分析类型的可能性是通过“双重标准函数”的设备从这个角度进行分析的。

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