长度偏差右删失数据下比例均值剩余寿命模型的估计方法

本文考虑了长度偏差右删失数据下均值剩余寿命模型的统计推断.当截断变量满足平稳性假设时,长度偏差右删失数据比左截断右删失数据具有更多的信息.为了提高参数估计的效率,我们在估计方程构造中添加了额外信息,通过组合方法获得了新的估计.模拟研究的结果也表明,组合估计方程的方法比仅考虑左截断右删失数据的方法更有效,结果表现更好.     

长度偏差右删失数据下[1mm]比例均值剩余寿命模型的估计方法

本文考虑了长度偏差右删失数据下均值剩余寿命模型的统计推断.当截断变量满足平稳性假设时,长度偏差右删失数据比左截断右删失数据具有更多的信息.为了提高参数估计的效率,我们在估计方程构造中添加了额外信息,通过组合方法获得了新的估计.模拟研究的结果也表明,组合估计方程的方法比仅考虑左截断右删失数据的方法更有效,结果表现更好.     

左截断数据下非线性模型的加权分位数回归

左截断数据是一类具有特殊结构的缺失数据,当且仅当研究变量大于一定的阈值时才能取得观察值.本文针对左截断数据下的非线性回归模型,提出了加权分位数估计方法,利用加权方式处理左截断缺失数据,取得了与完整数据相近的估计结果.并在一定假设条件下,证明了所提估计方法的一致性和渐近正态性等大样本性质,最后通过数值模拟展现所提估计方法的有限样本表现.     

约束条件下多元线性模型中线性估计的可容许性

本文研究了多元线性模型中未知参数在约束条件:(θ-θ0)′X′NX(θ-θ0)≤U,N≥0下中心点θ0对线性估计的可容许性的影响.研究结果表明对于具有某种结构的θ1和θ2,在约束集(θ-θ1)′X′NX(θ-θ1)≤U,N≥0与(θ-θ2)′X′NX(θ-θ2)≤U,N≥0下的可容许线性估计类是一致的.     

缺失数据下含几何分布的对数线性模型的EM算法

本文研究缺失数据下对数线性模型参数的极大似然估计问题.通过Monte-Carlo EM算法去拟合所提出的模型.其中,在期望步中利用Metropolis-Hastings算法产生一个缺失数据的样本,在最大化步中利用Newton-Raphson迭代使似然函数最大化.最后,利用观测数据的Fisher信息得到参数极大似然估计的渐近方差和标准误差.     

基于循序-Ⅰ型删失数据的Gompertz-sinh分布的统计推断(英文)

本文研究在循序-I型删失数据情形下Gompertz-sinh分布的统计推断问题.利用处理删失数据的EM算法,讨论Gompertz-sinh分布未知参数的最大似然估计(MLE)问题.为了讨论未知参数的近似置信区间估计,基于遗失信息原则,给出观测Fisher信息矩阵.为了演示本文的方法,给出相关数值模拟结果和一个真实数据实例.     

基于循序-I型删失数据的Gompertz-sinh分布的统计推断[英文]

本文研究了在循序-I型删失数据情形下Gompertz-sinh分布的统计推断问题.利用处理删失数据的EM算法,我们讨论了Gompertz-sinh分布未知参数的最大似然估计(MLE)问题.为了讨论未知参数的近似置信区间估计,基于遗失信息原则,我们给出了观测Fisher信息矩阵.为了演示本文的方法,我们给出了相关数值模拟结果和一个真实数据实例.     

含有溶质的流体在两层多孔介质中的渗流问题

本文讨论含有溶质的流体在两层多孔介质中的渗流问题，即（θ（x，U）t=（K（x，U）Ux-K（x，U））x，（x，t）∈GT，（θ（x，U）V（x，t）t=（DθVx）x-（V（KUx-K））x，（x，t）∈GT，U（x，0）=U0（x），V（x，0）=V0（x），0≤x≤2，U（0，t）-h0（t），U（2，t）=h2（t），0≤t≤T，V（0，t）=g0（t），V（2，t）=g2（t），0≤t≤T。其中θ（x,U)=θ1(x,U)，当（x,t)∈D1=｛0≤x≤1,0≤t≤T｝；θ（x,U)=θ2(x,U)当（x,t）∈D2＋1｛1＜x≤2，0≤t≤T｝。K（x,U)=K1(x,U)当（x,t)∈D1;K(x,U)=K2(x,U)，当(x,t)∈D2。θi，Ki分别是Di上的介质含水率及水力传导率，V是溶质的浓度，此外还要求U，V，K（x,U)(Ux-1)及DθVx V(KUx-K)在x=1连续。     

对左截断数据估计平稳序列

设平稳信号过程$\{X_t\}$被白噪声序列$\{Y_t\}$干扰. 只有$X_t>Y_t$时可以观测到信号过程$X_t$, 否则只能观测到白噪声$Y_t$. 这种数据模型被称为左截断数据模型. 本文在左截断数据模型下估计平稳信号过程的$\{X_t\}$均值, 自协方差函数, 和自相关系数. 证明所给的估计量是强相合估计. 当$X_t$是自回归序列时, 本文给出自回归模型的强相合的参数估计.     

随机截尾下污染数据部分线性模型的强相合估计

考虑一类新的污染数据部分线性模型,当受污染后的因变量被随机右截断时,就截断分布已知的情形,利用所获得截断观测数据构造了模型中的参数分量,非参数分量及污染系数的估计量,并在适当的条件下,证明了这些估计量的强相合性.     

Information in Quantal Response Data and Random Censoring

In this paper we study interesting properties of Fisher and divergence type measures of information for quantal, complete and incomplete random censoring, and not censoring at all. It is shown that, while quantal random censoring is less expensive, it is less informative than complete random censoring. It is also shown that in experiments which are mixtures of quantal and complete random censoring, the information received from these experiments is a convex combination of quantal information and the information in complete random censoring. Finally, the "total information" property is studied, in which the information received by the uncensored experiment can be expressed as the sum of the information provided by random censoring and the loss of information due to censoring. The results for Fisher's measure of information are an extension of already known results to the multiparameter case. The investigation of the previous information properties for divergence type measures is a new element, as well as the comparison of byproducts of Fisher information matrices.     

A lifetime model with increasing failure rate

This paper deals with a new two-parameter lifetime distribution with increasing failure rate. This distribution is constructed as a distribution of a random sum of independent exponential random variables when the sample size has a zero truncated binomial distribution. Various statistical properties of the distribution are derived. We estimate the parameters by maximum likelihood and obtain the Fisher information matrix. Simulation studies show the performance of the estimators. Also, estimation of the parameters is considered in the presence of censoring. A real data set is analyzed for illustrative purposes and it is noted that the distribution is a good competitor to the gamma, Weibull, exponentiated exponential, weighted exponential and Poisson-exponential distributions for this data set.     

A non-parametric competing risks model for manpower planning

One of the most important variables for manpower planners is duration until a specified event occurs. This is frequently the completed length of service until leaving a job, but may also include such variables as length of service in a grade until promotion, or length of a spell of withdrawal from the labour force. In this paper we develop non-parametric maximum likelihood estimators for the survivor functions of length of stay in a grade until leaving for a number of different possible destinations. Since the data are statistically incomplete, including right censored and left truncated durations, as well as complete durations, we must modify the competing risks theory in the biostatistical literature to take such incompleteness into account. Right censored durations arise when the individual is still in the grade when data collection ceases and left truncated durations when the individual is already in service when data collection commences. The competing risks model is fitted to data for Northern Ireland nursing service and used to predict staff flows between grades. We may thus estimate future movements within the system and predict the future manpower stocks.     

An information criterion for model selection with missing data via complete-data divergence

We derive an information criterion to select a parametric model of complete-data distribution when only incomplete or partially observed data are available. Compared with AIC, our new criterion has an additional penalty term for missing data, which is expressed by the Fisher information matrices of complete data and incomplete data. We prove that our criterion is an asymptotically unbiased estimator of complete-data divergence, namely the expected Kullback–Leibler divergence between the true distribution and the estimated distribution for complete data, whereas AIC is that for the incomplete data. The additional penalty term of our criterion for missing data turns out to be only half the value of that in previously proposed information criteria PDIO and AICcd. The difference in the penalty term is attributed to the fact that our criterion is derived under a weaker assumption. A simulation study with the weaker assumption shows that our criterion is unbiased while the other two criteria are biased. In addition, we review the geometrical view of alternating minimizations of the EM algorithm. This geometrical view plays an important role in deriving our new criterion.     

Exact Solutions of Fisher and Generalized Fisher Equations with Variable Coefficients

In this work,we consider a Fisher and generalized Fisher equations with variable coefficients.Usingtruncated Painlevé expansions of these equations,we obtain exact solutions of these equations with a constrainton the coefficients a(t)and b(t).     

Some results on a doubly truncated generalized discrimination measure

Doubly truncated data appear in some applications with survival and astrological data. Analogous to the doubly truncated discrimination measure defined by Misagh and Yari (2012), a generalized discrimination measure between two doubly truncated non-negative random variables is proposed. Several bounds are obtained. It is remarked that the proposed measure can never be equal to a nonzero constant which is independent of the left and right truncated points. The effect of monotone transformations on the proposed measure is discussed. Finally, a simulation study is added to provide the estimates of the proposed discrimination measure.     

Some inequalities related to the Stam inequality

Zamir showed in 1998 that the Stam classical inequality for the Fisher information (about a location parameter)

Fisher information under restriction of Shannon information in multi-terminal situations

Fisher information generally decreases by summarizing observed data into encoded messages. The present paper studies the amount of Fisher information included in independently summarized messages from correlated information sources; that is, the amount of Fisher information when sequences x ^N and y ^N of N independent observations of random variables x and y are encoded (summarized) independently of each other into meassages m _X and m _Y . The problem is to obtain the maximal amount of Fisher information when the size of the summarized data or Shannon message information is limited. The problem is solved in the case of completely compressed symmetric data summarization. An achievable bound is given in the general case. Information geometry, which is a powerful new differential geometrical method applicable to statistics and systems theory, is applied to this problem, proving its usefulness in information theory as well.The present work is supported in part by Grant-in-Aid for Scientific Research #61030014, Ministry of Education, Science and Culture of Japan.     

Reliability inference of stress–strength model for the truncated proportional hazard rate distribution under progressively Type-II censored samples

This paper considers the reliability inference for the truncated proportional hazard rate stress–strength model based on progressively Type-II censoring scheme. When the stress and strength variables follow the truncated proportional hazard rate distributions, the maximum likelihood estimation and the pivotal quantity estimation of stress–strength reliability are derived. Based on the percentile bootstrap sampling technique, the 95% confidence interval of stress–strength reliability is obtained, as well as the related coverage percentage. Moreover, based on the Fisher Z transformation and the modified generalized pivotal quantity, the 95% modified generalized confidence interval for the stress–strength reliability is obtained. The performance of the proposed method is evaluated by the Monte Carlo simulation. The numerical results show that the pivotal quantity estimators performs better than the maximum likelihood estimators. At last, two real datasets are analyzed by the proposed methodology for illustrative purpose. The results of real example analysis show that our model can be applied to the practical problem, the truncated proportional hazard rate distribution can fit the failure data better than other distributions, and the algorithms in this paper are suitable to handle the small sample data.