共查询到20条相似文献,搜索用时 31 毫秒
1.
2.
This paper concerns the study of asymptotic properties of the maximum likelihood estimator (MLE) for the general hidden semi-Markov
model (HSMM) with backward recurrence time dependence. By transforming the general HSMM into a general hidden Markov model,
we prove that under some regularity conditions, the MLE is strongly consistent and asymptotically normal. We also provide
useful expressions for asymptotic covariance matrices, involving the MLE of the conditional sojourn times and the embedded
Markov chain of the hidden semi-Markov chain. Bibliography: 17 titles. 相似文献
3.
为了提高指数分布产品可靠度的估计效率,研究了基于排序集抽样方法的极大似然估计量(Maximum likelihood estimator,MLE),证明了新MLE具有存在性、唯一性和渐近正态性,并通过排序集样本的Fisher信息得到MLE的渐近方差。针对似然方程没有显式解的问题,利用部分期望法对MLE进行修正,并给出其具体表达式。渐近相对效率和模拟相对效率的研究结果表明:排序集抽样下MLE和修正MLE的估计效率都一致高于简单随机抽样下MLE。最后,将推荐方法应用到转移性肾癌的临床研究中。 相似文献
4.
5.
Nakahiro Yoshida Toshiharu Hayashi 《Annals of the Institute of Statistical Mathematics》1990,42(3):489-507
Under some regularity conditions, it is well known that the maximum likelihood estimator (MLE) is asymptotically normal and efficient. However, if the observation is contaminated, the MLE is not always an appropriate estimator. In this paper, we treat M-estimators and study their asymptotic behavior. By choosing estimation equations, robust M-estimators are presented for phase parameters. 相似文献
6.
对非线性再生散度随机效应模型, 该文给出了类似于Barndroff-Nielson, Cox (1989)和Severin, Wong (1992)的正则条件, 基于这些正则条件和Laplace近似, 证明了该模型参数极大似然估计的存在性、强相合性和渐近正态性. 相似文献
7.
8.
一种Sieve极大似然估计的渐近性质 总被引:2,自引:0,他引:2
该文针对部分线性模型,在响应变量的观测值为Ⅰ型区间删失数据的情形下,讨论Sieve极大似然估计的渐近性质.用三角级数来构造Sieve空间,在一定条件下证明了该估计具有强相合性;得到了该估计的弱收敛速度,并且非参数部分的估计达到了最优收敛速度;还算出了参数部分的信息界. 相似文献
9.
本文讨论了如何去解决基于分组数据下的回归系数的估计问题.本文所讨论的基于分组数据下的回归模型与经典回归模型的差异在于因变量的观测值为分组数据,即我们只知道它落于事先确定的一组区间中的某一区间,而不知道它的具体值;而经典回归模型的因变量观测值则是一个确定的数值.我们用MLE去估计回归系数,但是此时的MLE无显式解,所以寻找一个合适的迭代算法就成了问题的关键.我们选择利用Bayes计算方法中的EM算法来获得估计量的迭代公式.随机模拟显示了所得估计的有效性. 相似文献
10.
Under some regularity conditions, the asymptotic expected deficiency (AED) of the maximum likelihood estimator (MLE) relative to the uniformly minimum variance unbiased estimator (UMVUE) for a given one-parameter estimable function of an exponential family is obtained. The exact expressions of the AED for normal, lognormal, inverse Gaussian, exponential (or gamma), Pareto, hyperbolic secant, Bernoulli, Poisson and geometric (or negative binomial) distributions are also derived. 相似文献
11.
On statistical models for regression diagnostics 总被引:2,自引:0,他引:2
In regression diagnostics, the case deletion model (CDM) and the mean shift outlier model (MSOM) are commonly used in practice. In this paper we show that the estimates of CDM and MSOM are equal in a wide class of statistical models, which include LSE, MLE, Bayesian estimate andM-estimate in linear and nonlinear regression models; MLE in generalized linear models and exponential family nonlinear models; MLEs of transformation parameters of explanatory variables in a Box-Cox regression models and so on. Furthermore, we study some models, in which, the estimates are not exactly equal but are approximately equal for CDM and MSOM. 相似文献
12.
13.
Yury A. Kutoyants 《Statistical Inference for Stochastic Processes》2017,20(3):347-367
This is a review of some recent results on parameter estimation by the continuous time observations for two models of observations. The first one is the so called signal in white Gaussian noise and the second is inhomogeneous Poisson process. The main question in all statements is: what are the properties of the MLE if there is a misspecification in the regularity conditions? We consider three types of regularity: smooth signals, signals with cusp-type singularity and discontinuous signals. We suppose that the statistician assumes one type of regularity/singularity, but the real observations contain signals with different type of singularity/regularity. For example, the theoretical (assumed) model has a discontinuous signal, but the real observed signal has cusp-type singularity. We describe the asymptotic behavior of the MLE in such situations. 相似文献
14.
The paper studies long time asymptotic properties of the Maximum Likelihood Estimator (MLE) for the signal drift parameter
in a partially observed fractional diffusion system. Using the method of weak convergence of likelihoods due to Ibragimov
and Khasminskii (Statistics of random processes, 1981), consistency, asymptotic normality and convergence of the moments are
established for MLE. The proof is based on Laplace transform computations. 相似文献
15.
Error bounds for asymptotic expansions of the distribution of the MLE in a GMANOVA model 总被引:1,自引:0,他引:1
Yasunori Fujikoshi 《Annals of the Institute of Statistical Mathematics》1987,39(1):153-161
Summary In this paper we obtain asymptotic expansions for the distribution function and the density function of a linear combination
of the MLE in a GMANOVA model, and for the density function of the MLE itself. We also obtain certain error bounds for the
asymptotic expansions. 相似文献
16.
《Statistics & probability letters》2007,77(16):1622-1627
We consider the asymptotic distribution of the maximum likelihood estimator (MLE), when the log-likelihood ratio statistic weakly converges to the non-degenerated Gaussian process. We provide a simple expression for the density function of the asymptotic distribution by fundamental stochastic results. This note is helpful to investigate asymptotic properties of the MLE in a certain non-regular case. 相似文献
17.
In this paper we study the Maximum Likelihood Estimator (MLE) of the vector parameter of an autoregressive process of order p with regular stationary Gaussian noise. We prove the large sample asymptotic properties of the MLE under very mild conditions. We do simulations for fractional Gaussian noise (fGn), autoregressive noise (AR(1)) and moving average noise (MA(1)). 相似文献
18.
Yoichi Nishiyama 《Annals of the Institute of Statistical Mathematics》1995,47(2):195-209
This paper deals with statistical inference problems for a special type of marked point processes based on the realization in random time intervals [0,u]. Sufficient conditions to establish the local asymptotic normality (LAN) of the model are presented, and then, certain class of stopping times u satisfying them is proposed. Using these stopping rules, one can treat the processes within the framework of LAN, which yields asymptotic optimalities of various inference procedures. Applications for compound Poisson processes and continuous time Markov branching processes (CMBP) are discussed. Especially, asymptotically uniformly most powerful tests for criticality of CMBP can be obtained. Such tests do not exist in the case of the non-sequential approach. Also, asymptotic normality of the sequential maximum likelihood estimators (MLE) of the Malthusian parameter of CMBP can be derived, although the non-sequential MLE is not asymptotically normal in the supercritical case. 相似文献
19.
In this paper, we propose a Markov regime-switching quantile regression model, which considers the case where there may exist equilibria jumps in quantile regression. The parameters are estimated by the maximum likelihood estimation (MLE) method. A simulation study of this new model is conducted covering many scenarios. The simulation results show that the MLE method is efficient in estimating the model parameters. An empirical analysis is also provided, which focuses on the detection of financial crisis contagion between United States and some European Union countries during the period of sub-prime crisis from the angle of financial risk. The degree of financial contagion between markets is subsequently measured by utilizing the quantile regression coefficients. The empirical results show that in a crisis situation, the interdependence between United States and European Union countries dramatically increases. 相似文献
20.
Michael G. Akritas 《Annals of the Institute of Statistical Mathematics》1982,34(1):259-280
Summary We consider consistency and asymptotic normality of maximum likelihood estimators (MLE) for parameters of a Lévy process of
the discontinuous type. The MLE are based on a single realization of the process on a given interval [0,t]. Depending on properties of the Lévy measure we either consider the MLE corresponding to jumps of size greater than ε and,
keepingt fixed, we let ε tend to 0, or we consider the MLE corresponding to the complete information of the realization of the process
on [0,t] and lett tend to ∞. The results of this paper improve in both generality and rigor previous asymptotic estimation results for such
processes. 相似文献