日期精度：到日 3 篇 · 到月 3 篇 · 到年 2 篇
自回归移动平均方程的严格平稳解
Necessary and sufficient conditions for the existence of a strictly stationary solution of the equations defining an autoregressive moving average process driven by an independent and identically distributed noise sequence are determined. No moment assumptions on the driving noise sequence are made.
正则非遍历模型的渐近条件推断及其自回归应用
A conditional limit theorem is derived for a certain class of stochastic processes whose distributions constitute a nonergodic family. The limit theorem allows us to study the asymptotic behaviour under the conditional model of some standard statistical procedures by making use of results for ergodic families. Explosive Gaussian autoregressive processes are studied in some detail. Here the conditional process is shown to be a nonexplosive Gaussian autoregression bearing a…
非递减 Lévy 过程的非参数估计
Summary Three non-parametric estimates of the measure corresponding to a non-decreasing Lévy process are discussed. Consistency and the limit distributions of the estimates are studied. The empirical process corresponding to one of the estimates is briefly discussed with an anticipation of an application to goodness-of-fit tests.
正稳定分布的高效率估计
A moment method based on the sample averages of X -t and X -2t (with suitably chosen t) is suggested for estimating the index a and scale parameter c 1/α of the positive stable distribution with Laplace transform E exp(-ΛX) = exp(-cΛα). The corresponding Cramér-Rao lower bounds are computed by using a new and simple Fourier technique, which is based on an idea of Jarrett. It is found that the asymptotic efficiencies of the proposed estimators exceed .97 for all values of α…
伽马过程与稳定过程参数估计的一则札记
Maximum likelihood estimators of the parameters of nondecreasing pure-jump gamma and stable processes based on the jumps of size greater than or equal to ε were studied in a previous paper (Basawa & Brockwell, 1978). In particular, for a single realization {X( u ), 0 ≤ u ≤ t }, the estimators for the stable process are consistent as ε ↓ 0, but this is not so for the gamma process. In the present note we derive asymptotic distributions as ε ↓ 0 for these estimators, centred…
关于伽马过程与稳定过程估计的一个注记
Maximum likelihood estimators of the parameters of nondecreasing pure-jump gamma and stable processes based on the jumps of size greater than or equal to ε were studied in a previous paper (Basawa & Brockwell, 1978). In particular, for a single realization {X( u ), 0 ≤ u ≤ t }, the estimators for the stable process are consistent as ε ↓ 0, but this is not so for the gamma process. In the present note we derive asymptotic distributions as ε ↓ 0 for these estimators, centred…
Gamma 与稳定过程的统计推断
Problems of estimation and testing for nondecreasing pure jump gamma and stable additive processes are considered. The inference is based on a single realization of the process on a given time interval [0,t]. The maximum likelihood estimators of the parameters based on observation of the jumps of size greater than or equal to ε are found to be consistent as ε tends to 0 for the stable process but not for the gamma process.
伽马过程与稳定过程的统计推断
Problems of estimation and testing for nondecreasing pure jump gamma and stable additive processes are considered. The inference is based on a single realization of the process on a given time interval [0,t]. The maximum likelihood estimators of the parameters based on observation of the jumps of size greater than or equal to ε are found to be consistent as ε tends to 0 for the stable process but not for the gamma process.