论文标题
$ p $ -spin curie-weiss模型中最大似然估计的相变
Phase Transitions of the Maximum Likelihood Estimates in the $p$-Spin Curie-Weiss Model
论文作者
论文摘要
在本文中,我们考虑了$ p $ -spin curie-weiss模型中的参数估计问题,$ p \ geq 3 $。我们提供了最大可能性(ML)反向温度和磁场的限制属性的完整描述,从$ p $ -spin curie-weiss模型实现了单一的实现,并补充了2型旋转案例中众所周知的结果(Comets and Gidas(1991))。我们的结果发现了各种新的相变和令人惊讶的限制定理,例如参数空间中“临界”曲线的存在,其中ML估计的限制分布是具有连续和离散成分的混合物。混合组件的数量为2或三个,具体取决于参数之一的标志和$ p $的奇偶校验。另一个有趣的启示是,在参数空间中存在某些“特殊”点,其中ML估计表现出了外度现象,并以$ n^{\ frac {\ frac {3} {4}} $收敛到非高斯限制分布。使用这些结果,我们可以在参数空间中所有点的逆温度和磁场上获得渐近有效的有效置信区间,其中可能是一致的估计。
In this paper we consider the problem of parameter estimation in the $p$-spin Curie-Weiss model, for $p \geq 3$. We provide a complete description of the limiting properties of the maximum likelihood (ML) estimates 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 (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 estimates 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 estimates exhibit a superefficiency phenomenon, converging to a non-Gaussian limiting distribution at rate $N^{\frac{3}{4}}$. 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.