标记Gibbs点过程指数族模型的最大伪随机估计
Maximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes
摘要：
本文利用最大拟似然方法，对Gibbs点过程的能量函数的参数化向量$\bm θ$进行了估计.给出了依赖于单一实现的估计量的强相合性和渐近正态性结果。在指数族模型的框架内，充分条件表示在当地的能量函数，并验证了各种各样的例子。
英文摘要：
This paper is devoted to the estimation of a vector $\bm θ$ parametrizing an energy function of a Gibbs point process, via the maximum pseudolikelihood method. Strong consistency and asymptotic normality results of this estimator depending on a single realization are presented. In the framework of exponential family models, sufficient conditions are expressed in terms of the local energy function and are verified on a wide variety of examples.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
