Phase transitions of the maximum likelihood estimators in the p-spin Curie-Weiss model

被引:0
作者
Mukherjee, Somabha [1 ]
Son, Jaesung [2 ]
Bhattacharya, Bhaswar b. [3 ]
机构
[1] Natl Univ Singapore, Dept Stat & Data Sci, Singapore, Singapore
[2] Columbia Univ, Dept Stat, New York, NY 10027 USA
[3] Univ Penn, Dept Stat & Data Sci, Philadelphia, PA USA
关键词
Central limit theorems; estimation; Ising models; magnetization; phase transitions; spin-systems; superefficiency; ISING-MODELS; INFERENCE; FIELDS;
D O I
10.3150/24-BEJ1779
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper we consider the problem of parameter estimation in the p-spin Curie-Weiss model, for p >= 3. We provide a complete description of the limiting properties of the maximum likelihood (ML) estimators of the inverse temperature and the magnetic field given a single realization from the p-spin Curie-Weiss model, complementing the well-known results in the 2-spin case by Comets and Gidas (1991). Our results unearth various new phase transitions and surprising limit theorems, such as the existence of a 'critical' curve in the parameter space, where the limiting distribution of the ML estimators is a mixture with both continuous and discrete components. The number of mixture components is either two or three, depending on, among other things, the sign of one of the parameters and the parity of p. Another interesting revelation is the existence of certain 'special' points in the parameter space where the ML estimators exhibit a superefficiency phenomenon, converging to a non-Gaussian limiting distribution at rate N3/4. Using these results we can obtain asymptotically valid confidence intervals for the inverse temperature and the magnetic field at all points in the parameter space where consistent estimation is possible.
引用
收藏
页码:1502 / 1526
页数:25
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