论文检索

摘要暂缺

摘要暂缺

ARMA 模型中的镜像与不变分布AI 解读

The finite sample distributions of estimators and test statistics in ARMA time series models are generally unknown. For typical sample sizes, the approximations provided by asymptotic distributions are often unsatisfactory. Hence simulation or numerical integration methods are used to investigate the distributions. In practice only a limited part of the parameter space is examined using these methods. Thus any results which allow us to infer properties from one portion of…

摘要暂缺

摘要暂缺

一阶移动平均模型最大似然估计量的小样本性质AI 解读

In this paper we discuss finite sample properties of the maximum likelihood estimator θ^ in the first-order moving average model. We give a theoretical explanation for the concentration of θ^ values at the invertibility boundary. We derive the exact distribution of θ^ for sample size n=2 which is found to be of mixed type. For general n we give approximations for pr (⁠θ^=1).

单调百分位数回归AI 解读

Suppose that for each number $t$ in [0, 1] there is a distribution with distribution function $F_t(\bullet)$ which has $p$th percentile $\xi(t)$. Consider the problem of estimating $\xi(\bullet)$ under the assumption that $\xi(\bullet)$ is monotone. An estimator which is analogous to the median regression estimator considered in Cryer, Robertson, Wright and Casady (1972), is studied. Asymptotic properties including consistency and law of the iterated logarithm results are…