共查询到20条相似文献，搜索用时 203 毫秒
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著名学者西奇尔的广义逆高斯—泊松过程分布是在情报计量模型中应用较为广泛的,具有理论研究的吸引力,由于许多情报计量数据集对于零范畴认识不足,影响了建模,文章针对其不足,推导出极大似然估计程序,克服了建模计算上的困难,使逆高斯—泊松过程分布和情报计量数据集达到较好的拟合。 相似文献
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对基于均衡约束数学规划(MPEC)的数据分类模型进行改进.在确定数据所服从分布的密度函数(高斯混合模型来模拟)的参数时,使用β似然估计来代替原模型中的最大似然估计.新模型可以克服似然函数可能出现无界的现象,在计算上有更好的鲁棒性.对于所得MPEC分类模型,使用filterSQP方法将其作为非线性规划求解.数值试验显示了新模型的有效性. 相似文献
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巨灾的频繁发生已引起了社会各界的高度关注。本文应用阈顶点模型(Peaks over threshold,POT)和广义帕累托分布(generalized pareto distribution,GPD),对我国1969—2012年间的地震直接经济损失数据进行拟合,利用不同方法探讨了最优阈值的选取问题,并采用极大似然法对GPD分布的参数进行了估计。经检验发现POT模型拟合巨灾风险厚尾部分的效果较好。文章还探索了POT模型在VaR上的应用,并提出用CVaR、PML这2种风险测度指标来改善VaR。最后利用复合泊松分布的可分解性及实际损失额在不同起赔点下具有的不同分布函数的事实,充分考虑了不同情况下纯保费的计算。 相似文献
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文章利用极值理论对我国某省商业银行欺诈风险损失数据进行极值分布研究,通过对尾部参数的无偏估计,改进的POT模型估计方法估计操作风险尾部形状参数,采用超额均值函数估计阈值、极大似然法估计尺度参数,利用估计值得到欺诈风险损失的尾部分布函数,从而估计出在99.9%置信区间下的欺诈风险在险价值,为配置覆盖资本作参考. 相似文献
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传统方法在对网络拓扑结构可靠性进行评估的过程中,存在参数方向不明确的问题,提出基于极大似然函数的独立分布网络拓扑结构可靠度评估模型。利用Weibull函数代表故障率模型,分析网络部件故障率的时间曲线,并构建网络节点和链路效能的时变模型,获得独立分布网络的时间效能模型;计算独立分布网络的拓扑结构函数,获得网络的开失效和短失效概率,根据极大似然估计对参数的偏导数进行求取,可以获得似然方程,利用得到的偏导数来构建独立分布网络拓扑结构可靠度评估模型,最终实现对独立分布网络拓扑结构可靠度的评估。实验结果得知,提出方法在对独立分布网络拓扑结构可靠度进行评估时,测试结果与期望输出结果的拟合度较高,并且评估时间较短,验证了模型的有效性。 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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基于2010—2019年珠三角上市企业的数据,构建一个有调节的中介效应模型,运用零膨胀因子的泊松回归模型考察区域创新政策如何影响企业创新绩效.结果发现:政策力度和政策数量都对企业创新绩效起到促进作用,但作用不大;在区域创新政策影响企业创新绩效过程中,企业研发投入起到明显的部分中介作用,区域创新政策对企业创新活动具有明显... 相似文献
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This paper studies the distributed Kalman consensus filtering problem based on the event-triggered (ET) protocol for linear discrete time-varying systems with multiple sensors. The ET strategy of the send-on-delta rule is employed to adjust the communication rate during data transmission. Two series of Bernoulli random variables are introduced to represent the ET schedules between a sensor and an estimator, and between an estimator and its neighbor estimators. An optimal distributed filter with a given recursive structure in the linear unbiased minimum variance criterion is derived, where solution of cross-covariance matrix (CCM) between any two estimators increases the complexity of the algorithm. In order to avert CCM, a suboptimal ET Kalman consensus filter is also presented, where the filter gain and the consensus gain are solved by minimizing an upper bound of filtering error covariance. Boundedness of the proposed suboptimal filter is analyzed based on a Lyapunov function. A numerical simulation verifies the effectiveness of the proposed algorithms. 相似文献
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《Journal of The Franklin Institute》2023,360(12):9139-9158
The consensus tacking problem for multi-agent systems with a leader of none control input and unknown control input is studied in this paper. By virtue of the relative state information of neighboring agents, state estimator and disturbance estimator are designed for each follower to estimate the system states and exogenous disturbance, respectively. Meanwhile, a novel control protocol based on two estimators is designed to make tracking error eventually converge to zero. Furthermore, the obtained results are further extended to the leader with unknown control input. A novel state estimator with adaptive time-varying gain is proposed such that consensus tracking condition is independent of the Laplacian matrix with regard to the communication topology. Finally, two examples are presented to verify the feasibility of the proposed control protocol. 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
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This paper aims at time-series prediction of disease counts when the trend changes unexpectedly. There is a body of literature in time-series analysis that focuses on improving the prediction when a change in the trend is observed. Following this line of literature, a method was recently proposed that outperforms the previous proposals. To utilize this method for prediction of disease counts, the present study employs a commonly used method called local estimators for estimation near boundaries. This provides two advantages for disease count prediction. First, the prior method is limited to only smooth trend changes. However, the current study using local estimators also encounters abrupt changes. Taking both smooth and abrupt changes into account is important in predicting disease counts, because, for variety of different reasons, such as vaccination programs, the disease counts may encounter abrupt changes. Second, the current study, despite the previous approach, can also model uncertainty. The parameter uncertainty plays a significant role when predicting disease counts. Compared to current literature, the proposed method outperformed to predict counts for 12 diseases in Nevada. The paper demonstrates that the proposed methods improved the prediction Q-Score in comparison to both outbreak and structural change methods available in literature. Although this method has been specifically demonstrated for prediction of disease counts, it can be generalized for different applications. With the recent utilization of analytics techniques and the increased use of time-series analysis in information systems, the suggested method provides implications for the literature of information systems when predicting with structural trend changes in data. 相似文献
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对于一个参数进行估计来讲,不仅要考虑估计的精度,还要考虑所得到的估计对于模型拟合的优良程度。通常的损失函数无能为力,而平衡损失函数可以考虑到这两点,本文将在平衡误差损失函数下研究广义Pareto分布参数的Bayes估计问题。在平衡损失函数下导出了参数的Bayes估计并讨论了一类线性形式估计的可容许性和不可容许性。 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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Shi Liang Zhenyu Liu Chan Qiu Jianrong Tan 《Journal of The Franklin Institute》2018,355(14):6657-6674
This paper focuses on state estimation issues for networked control systems (NCSs) with both control input and observation packet dropouts over user datagram protocol (UDP) communication channels. For such systems, which are usually known as UDP-like systems, the computation cost of the optimal estimator is too high to afford in practice due to exponential growth of complexity. Although quite a few suboptimal estimators could be alternatives for improving the computational efficiency, yet researches on the stability of suboptimal estimators are rarely reported. Based on the generalized pseudo-Bayesian (GPB) algorithm, an efficient suboptimal algorithm is developed for UDP-like systems. More crucially, a sufficient condition is obtained, which guarantees the stability of its mean estimation error covariance. This stability condition explicitly expresses that the rate of observation packet dropout is a critical factor in determining the stability of the proposed GPB estimator, while the rate of control input packet dropout has no influence on it. The results are illustrated by numerical examples. 相似文献
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《Journal of The Franklin Institute》2018,355(18):9224-9244
In this paper a new approach to algebraic parameter identification of the linear SISO systems is proposed. The standard approach to the algebraic parameter identification is based on the algebraic derivatives in Laplace domain as the main tool for algebraic manipulations like elimination of the initial conditions and generation of linearly independent equations. This approach leads to the unstable time-varying state-space realization of the filters for the on-line parameter estimation. In this paper, the finite difference and shift operators in combination with the frequency-shifting property of Laplace transform is applied instead of algebraic derivatives. Resulting state-space realization of the estimator filters is asymptotically stable and doesn’t require switch-of mechanism to prevent overflow of the estimator variables. The proposed method is especially suitable for applications in closed-loop on-line identification where the stable behavior of the estimators is a necessary requirement. The efficiency of the proposed algorithm is illustrated on three simulation examples. 相似文献
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《Journal of The Franklin Institute》2022,359(8):3831-3856
Aiming at early detection of faults in dynamic systems subject to external periodic disturbances, this paper proposes a new generalized proportional-integral observer (GPIO) fault detection scheme with zero-pole joint optimization and novel complex coefficient gain (CCG) of residual evaluation. The focus of the proposed scheme is to reduce the adverse impacts caused by the semi-stationary periodic disturbance whose spectrum is uneven, with most energy being at some dominant frequencies. The proposed GPIO with a complex coefficient gain is designed in a two-stage procedure. In the first stage of zero assignment and pole optimization, the additional zeros introduced by the GPIO’s integration action are allocated to near the disturbance frequency. The gain of the transfer function matrix relating from the disturbances to the fault indicator signals is minimized by pole optimization. In the second stage of designing complex coefficient gain in residual evaluation, the unique feature of rank-deficient caused by the additional zeros assigned in stage one is further exploited to cancel the disturbances in the fault indicator signals (which is also referred to as the fault detection residual in this article). It is proved that, for an arbitrary periodic disturbance with a specific spectrum, the remnant components of the disturbance in the indicator signals generated by the GPIO can cancel each other by a complex gain vector, which can be determined by the zero eigenvalue’s left eigenvector of the rank-deficient of the disturbance transfer function matrix. The sufficient conditions for the convergence of the proposed fault detection filter are also given. Numerical examples illustrate the proposed method’s better performance in detecting minor faults. 相似文献
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J.M. Lowerre 《Journal of The Franklin Institute》1977,303(6):517-526
For the linear statistical model y = Xb + e, X of full column rank estimates of b of the form (C + X′X)+X′y are studied, where C commutes with X′X and Q+ is the Moore-Penrose inverse of Q. Such estimators may have smaller mean square error, component by component than does the least squares estimator. It is shown that this class of estimators is equivalent to two apparently different classes considered by other authors. It is also shown that there is no C such that (C + X′X)+X′Y = My, in which My has the smallest mean square error, component by component. Two criteria, other than tmse, are suggested for selecting C. Each leads to an estimator independent of the unknown b and σ2. Subsequently, comparisons are made between estimators in which the C matrices are functions of a parameter k. Finally, it is shown for the no intercept model that standardizing, using a biased estimate for the transformed parameter vector, and retransforming to the original units yields an estimator with larger tmse than the least squares estimator. 相似文献