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JOURNALS // Teoriya Veroyatnostei i ee Primeneniya // Archive

Teor. Veroyatnost. i Primenen., 1967 Volume 12, Issue 3, Pages 418–425 (Mi tvp724)

This article is cited in 20 papers

An asymptotic expansion for the distribution of the maximum likelihood estimation of a vektor parameter

N. M. Mitrofanova

Leningrad

Abstract: Let $X$ he a random variable with a distribution function $f(x,\theta)$ depending on a vector parameter $\theta=(\theta,\dots,\theta_r)$. Let $\widehat\theta_n$ be the maximum likelihood estimate of $\theta$ corresponding to a sample of size $n$. It is proved that under certain conditions on $f(x,\theta)$ the distribution function of $\widehat\theta_n$ has an asymptotic expansion on $n^{1/2}$ with the number of terms depending on properties of $f(x,\theta)$.

Received: 05.07.1966


 English version:
Theory of Probability and its Applications, 1967, 12:3, 364–372

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© Steklov Math. Inst. of RAS, 2025