共查询到19条相似文献,搜索用时 62 毫秒
1.
当分布密度的形式未知时,参数的极大似然估计没有明确的解析表达式,也不能通过设计算法由计算机运算得到。本文我们将从该分布中抽取的样本当作是来自另一个形式已知的分布密度的样本,该已知分布密度的选取依赖于未知的分布密度,但是具有与未知分布相似的边界性质。基于这两个分布族,我们提出了拟极大似然估计的概念,同时,对这种拟极大似然估计的渐近性质进行了讨论。结果表明拟极大拟然估计与极大似然估计有关相同的渐近性质,并且由于拟极大似然估计的获得不依赖于未知分布密度的形式,只与一已知的分布密度有关,使得通过计算机可以实现对其的求解。 相似文献
2.
本文研究了带有固定效应的空间误差面板数据模型的经验似然推断问题.利用经验似然方法,通过鞅差序列将空间误差面板数据模型估计方程中的二次型转化为线性形式,构造了空间误差面板数据模型参数的经验似然比统计量,得到了统计量的极限分布. 相似文献
3.
《数学的实践与认识》2015,(21)
在带自适应设计的拟似然非线性模型中,在响应变量的矩条件尽可能弱和其它正则条件下,证明了以概率为1,当n充分大时,拟似然方程有一个解βn,它收敛于参数真值β0. 相似文献
4.
林路 《数学物理学报(A辑)》1998,(Z1)
该文证明了,在非线性回归模型中,若以均方误差或均方误差矩阵为标准,拟似然估计是正则广义拟似然估计类中的最优估计,并讨论了拟得分函数最优性与拟似然估计最优性的关系.为改进拟似然估计,该文提出了一种约束拟似然估计,并证明了约束拟似然估计比拟似然估计有较小的均方误差. 相似文献
5.
6.
极大似然估计算法研究 总被引:3,自引:0,他引:3
将解一元方程的二分法推广至求解多元非线性方程组.以第K个变元Xk为参数,则κ元方程组就可以看作曲线s(前κ-1个方程)和κ-1维曲面C(第κ个方程),于是κ元方程组的解就可以看作寻找曲线s和曲面C的交点.对参数Xk作二分法,重复迭代,直到找到满足误差要求的方程组的解.最后给出了用多元二分法的算法求解极大似然估计的数值解. 相似文献
7.
8.
ARMA模型变化点的极大似然估计 总被引:1,自引:0,他引:1
设W_1,…W_(n-1),W_n,…,W_m是对系统S的无间断等时间间隔的K维观测向量,样本W_1,…,W_(n-1)和样本W_n,…,W_m相互独立且分别来自两个不同的ARMA模型: 相似文献
9.
利用方开泰和王元(1989)提出的序贯数论方法的一个优化算法(SNTO),本文给出求统计分布参数的极大似然估计的一个统一方法。为了说明这个方法的运用,我们集中处理威布尔和贝它分布的参数极大似然估计。许多例子表明,我们的方法是普遍有用和有效的。 相似文献
10.
讨论了一类参数空间受样本限制的极大似然估计问题.分析了随机变量分布的非零区域与似然函数定义域的对应关系,提出如果分布的非零区域受参数限制,则无论似然方程是否可解,参数的极大似然估计必然与样本顺序统计量X_((n))或X_((1))有关,并具体分析了似然估计一定等于、一定不等于和可能等于顺序统计量X_((n))(X_((1)))的三种情形,并给出了相应的判别条件.最后分析得出在第三种判别条件之下,似然估计是否取值于x_((n))(x_((1)))视具体的样本观测值决定. 相似文献
11.
Jaroslav Mohapl 《Annals of the Institute of Statistical Mathematics》1998,50(1):165-186
The article presents a central limit theorem for the maximum likelihood estimator of a vector-valued parameter in a linear spatial stochastic difference equation with Gaussian white noise right side. The result is compared to the known limit theorems derived for the approximate likelihood e.g. by Whittle (1954, Biometrika, 41, 434-439), Guyon (1982, Biometrika, 69, 95-105) and Rosenblatt (1985, Stationary Sequences and Random Fields, Birkhäuser, Boston) and to the asymptotic properties of the quasi-likelihood studied by Heyde and Gay (1989, Stochastic Process. Appl., 31, 223-236; 1993, Stochastic Process. Appl., 45, 169-182). Application of the theory is demonstrated on several classes of models including the one considered by Niu (1995, J. Multivariate Anal., 55, 82-104). 相似文献
12.
13.
本文对时变系数的空间面板数据模型进行了研究,所研究的模型利用扰动项中的空间个体成分将不同时期的方程联系起来,同时,自变量系数和空间自回归系数是时变的,但不会随着观测个体的变动而变动。本文利用基于可行的广义最小二乘估计的多阶段方法对模型参数进行了估计,研究了估计量的大样本性质,并利用Monte Carlo方法模拟了其小样本性质。模拟结果表明,估计量的渐近性质随着样本容量的增加而改善。对中国省级地区间财税策略互动行为的实证案例也体现了本文理论模型的应用价值。 相似文献
14.
The Markov-switching GARCH model allows for a GARCH structure with time-varying parameters. This flexibility is unfortunately undermined by a path dependence problem which complicates the parameter estimation process. This problem led to the development of computationally intensive estimation methods and to simpler techniques based on an approximation of the model, known as collapsing procedures. This article develops an original algorithm to conduct maximum likelihood inference in the Markov-switching GARCH model, generalizing and improving previously proposed collapsing approaches. A new relationship between particle filtering and collapsing procedures is established which reveals that this algorithm corresponds to a deterministic particle filter. Simulation and empirical studies show that the proposed method allows for a fast and accurate estimation of the model. 相似文献
15.
16.
This paper is concerned with an observation-driven model for time series of counts whose conditional distribution given past observations follows a Poisson distribution.This class of models is capable of modeling a wide range of dependence structures and is readily estimated using an approximation to the likelihood function. Recursive formulae for carrying out maximum likelihood estimation are provided and the technical components required for establishing a central limit theorem of the maximum likelihood estimates are given in a special case.AMS 2000 Subject Classification: Primary 62M05; Secondary 62E20 相似文献
17.
Y. T. Chan B. H. Lee S. M. Thomas 《Journal of Optimization Theory and Applications》2005,125(3):723-734
The estimation of a circles centre and radius from a set of noisy measurements of its circumference has many applications. It is a problem of fitting a circle to the measurements and the fit can be in algebraic or geometric distances. The former gives linear equations, while the latter yields nonlinear equations. Starting from estimation theory, this paper first proves that the maximum likelihood (ML), i.e., the optimal estimation of the circle parameters, is equivalent to the minimization of the geometric distances. It then derives a pseudolinear set of ML equations whose coefficients are functions of the unknowns. An approximate ML algorithm updates the coefficients from the previous solution and selects the solution that gives the minimum cost. Simulation results show that the ML algorithm attains the Cramer-Rao lower bound (CRLB) for arc sizes as small as 90°. For arc sizes of 15° and 5° the ML algorithm errors are slightly above the CRLB, but lower than those of other linear estimators.Communicated by L. C. W. Dixon 相似文献
18.
19.
Samuel Kotz Tomasz J. Kozubowski Krzysztof Podgórski 《Annals of the Institute of Statistical Mathematics》2002,54(4):816-826
Maximum likelihood estimators (MLE's) are presented for the parameters of a univariate asymmetric Laplace distribution for all possible situations related to known or unknown parameters. These estimators admit explicit form in all but two cases. In these exceptions effective algorithms for computing the estimators are provided. Asymptotic distributions of the estimators are given. The asymptotic normality and consistency of the MLE's for the scale and location parameters are derived directly via representations of the relevant random variables rather than from general sufficient conditions for asymptotic normality of the MLE's. 相似文献