共查询到18条相似文献，搜索用时 234 毫秒
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提出非齐次等式约束线性回归模型回归系数的一个新的有偏估计,即综合条件岭估计,讨论了综合条件岭估计的性质,在一定的条件下,综合条件岭估计的样本总方差、均方误差、均方误差矩阵均分别小于约束最小二乘估计的相应误差.在综合条件岭估计下,条件岭估计和条件根方估计为其特例,从而统一了条件岭估计和条件根方估计的理论. 相似文献
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信号噪声比率（SNR）估计是在时变衰落信道环境下相移键控通信系统的重要指标,目前有两种可实现的估计方法：数据辅助估计和非数据辅助估计。时变衰落信道可以建立为一个关于时间的多项式模型。传统的估计方法精度受限于Cramer—Rao下界信道,信道时变特性对于SNR估计的影响可以忽略。目前,一种新颖的最大似然（ML）SNR估计方法是由时变衰落模型推导而来的。对于DA场景估计来说,有一种简易的闭环估计方案,其准确性能评估依赖于正确与错误（不匹配）的多项式阶数。对于NDA估计,未知的数据符号建立为随机的模型,利用了边缘似然估计方法。最大期望算法通过迭代方法使得似然函数最大。仿真结果表明,相比先前公布的算法实现,该估计算法统计效率更高。 相似文献
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文章简要介绍了线性模型Ｍ估计（包括ＬＳ和Ｌ１估计）大样本理论研究状况,提出了一些有待解决的重要问题。 相似文献
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高维度在许多统计学问题中是很常见的。用渐近框架来查验协方差矩阵估计,随着样本容量n的增加,维度p趋向∞。由于p和K对基于模型的协方差矩阵估计器性能的影响,在适当的假设下,证实了这种基于模型的协方差矩阵估计器的收敛速度和渐近正态性。我们将该估计器的性能与样本协方差矩阵的性能进行了对比,明确了该因子法在哪些情况下从本质上提高了或轻微地提高了其性能。 相似文献
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回归系数一类线性估计的小样本性质 总被引：1，自引：0，他引：1
提出了线性模型中回归系数的一类线性估计.在均方误差矩阵(MSEM)准则和Pitman Closeness(PC)准则下,研究了这类线性估计相对于最小二乘(LS)估计的优良性.最后,讨论了当设计阵为非列满秩时,回归系数的可估函数的一类线性估计的优良性. 相似文献
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本文在加权平方损失下导出了平衡的双向分类随机效应模型中方差分量的Bayes估计,并利用 非参数方法构造了方差分量的经验Bayes (EB)估计。在适当的条件下证明 了EB估计的收敛速度。最后,给出一个满足主要结果的例子。 相似文献
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滑动平均模型（MA模型）是最常用的平稳序列模型之一,文章在模型阶数已知的情况下,重点研究MA模型中未知参数的逆相关估计、新息估计和矩估计,进行仿真计算,并对计算结果进行比较分析。 相似文献
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泊松回归模型常常用于计数数据的研究中,然而在实际数据中零值的比例可能远远大于泊松分布中取零值的概率,而且这些零值通常都有其特殊含义.此外计数数据可能是分组数据,即观测到的数据不是确切值而只是已知其落在某一个区间范围之内;或者某些特定的数据,例如工资,要先对它进行人为的分组然后再进行分析.考虑一种零膨胀泊松半参数回归模型来处理上述分组计数数据.该模型中泊松分布的期望与协变量之间采用部分线性连接函数,而零值的概率与协变量之间采用线性连接函数.利用Sieve极大似然估计方法来估计该回归模型中参数和非参数函数,并提出了一种得分检验方法来检验是否存在零膨胀.在一定正则条件下,获得了Sieve极大似然估计的渐近性质,证明了参数部分的估计是强相合,渐近正态及渐近有效的;同时非参数函数的估计达到了最优收敛速度.模拟研究表明,估计和检验方法效果都比较好,最后将此模型和推断方法应用于一组公共卫生领域实际数据研究. 相似文献
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赵超 《中国科学院研究生院学报》2010,27(4):556-562
用于估计马斯京根模型参数的方法很多,但这些方法在数据存在异常值时缺乏抵御异常值影响的抗差性能. 推导出一种有限制条件的参数抗差估计算法,通过含有随机误差和异常误差的人工数据和真实数据比较抗差算法与传统最小二乘算法的抗差性. 研究表明抗差估计算法能减小异常值对参数估值的影响. 相似文献
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The stochastic minimum-variance pseudo-unbiased reduced-rank estimator (stochastic MV-PURE estimator) has been developed to provide linear estimation with robustness against high noise levels, imperfections in model knowledge, and ill-conditioned systems. In this paper, we investigate the theoretical performance of the stochastic MV-PURE estimator under varying levels of additive noise. We prove that the mean-square-error (MSE) of this estimator in the low signal-to-noise (SNR) region is much smaller than that obtained with its full-rank version, the minimum-variance distortionless estimator, and the gap becomes larger as the noise level increases. These results shed light on the excellent performance of the stochastic MV-PURE estimator in highly noisy settings obtained in simulations so far. Furthermore, we extend previous numerical simulations to show how the insight gained from the results of this paper can be used in practice. 相似文献
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This paper proposes a design framework of sensor communication by using the stochastic event triggers, which aims at best saving the communication resources. The system to be considered is as follows: a sensor takes measurements of the states of a dynamic process and sends the information to a remote estimator, and the estimator computes the state estimates for the dynamic process. To save communication resources, a set of stochastic event triggers on the measurements are assigned to the sensor. At each sampled time, when no trigger is triggered, the sensor sends nothing to the estimator; when one of them is triggered, the sensor sends the identity code of the corresponding trigger. It is shown that once the estimator receives the identity of the trigger, it is equivalent for the estimator to receiving a measurement from a certain virtual sensor. Based on it, the system performance under the proposed communication is analyzed, and the design of specific models is considered. Examples are presented to demonstrate the proposed communication design. 相似文献
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《Journal of The Franklin Institute》2022,359(2):1569-1584
This paper studies centralized fusion estimation over a wireless sensor-actuator network, where packet dropouts cannot be observed by the fusion estimator. For such a system, we obtain an optimal linear fused estimation of system states, also known as optimal linear estimator. Then, we establish a necessary and sufficient condition for the stability of the optimal linear estimator. Finally, we show that the estimation performance is monotonically decreasing with respect to the observation packet-arrival rate. By analyzing a sequence that converges to the covariance of the optimal linear estimator, an analytical relationship between the estimation performance and the control packet-arrival rate is obtained. Simulation examples are given to illustrate the main results. 相似文献
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In this paper, a constrained regularized least square (RLS) state estimator is developed for deterministic discrete-time nonlinear dynamical systems subject to a set of equality and/or inequality constraints. The stability of the estimation error is rigorously analyzed. The proposed estimator is then used to handle the important problem of secure communication. At the transmitting end, the output of the constrained unified chaotic system is used as a chaotic mask to achieve a satisfactory and typical secure communication scheme. The encrypted data signal is injected into the transmitter and simultaneously transmitted to the receiver through a public channel. At the receiving end, the constrained RLS estimator is used to reconstruct the states of the constrained unified chaotic system. Simulation results are presented to show the impact of the imposed constraints on the waveform and the pattern of the generated chaotic signal as well as the ability of the proposed estimator to synchronize the actual and estimated states of the constrained unified chaotic system. Moreover, the proposed estimator is applied to recover discrete signals such as digital images where computer simulation results are provided to show the effectiveness of the proposed estimation scheme. 相似文献
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《Journal of The Franklin Institute》2021,358(18):10193-10212
In this paper, the non-fragile state estimation problem is investigated for a class of continuous-time delayed complex networks. In the addressed complex network model, the outputs only from partial network nodes are used to fulfill the state estimation task. For improving the efficiency of resource utilization, a dynamic event-triggering mechanism is applied in the design of estimator, where an auxiliary time-varying parameter is introduced to dynamically modulate the triggering condition. Our intention is to obtain the gain parameters of the desired non-fragile state estimator, which can tolerate the norm-bounded gain perturbation. In virtue of a novel Lyapunov functional and matrix inequality technique, sufficient conditions are provided to ensure robustly exponential boundedness for estimation error dynamics, and gain matrices of the estimator are computed based on certain matrix inequalities. An illustrative simulation is presented to show the validity of the non-fragile estimator proposed. 相似文献
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In this paper, a new algebraic approach to the on-line signal derivatives estimation is proposed. The proposed approach is based on the conversion of the truncated Taylor series expansion to the set of linearly independent equations regarding the signal derivatives. The nonhomogeneous parts of the obtained set of equations are convolution integrals, which can be transformed to the stable linear state-space filter realization. The proposed algebraic estimator provides stable convergence without the need for periodic re-initialization, as in the case of the conventional algebraic estimators. In contrast to the Taylor series-based tracking differentiators, the proposed estimator also provides an estimation of the arbitrary number of the higher-order signal derivatives. In addition, the tuning of the estimator parameters does not depends on the filter dimension. The efficiency of the proposed estimator is illustrated by the simulation examples and experimental results related to the monitoring of the surgical drilling process. 相似文献