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排序方式: 共有48条查询结果,搜索用时 15 毫秒
1.
Keith Jonathan M. Kroese Dirk P. Bryant Darryn 《Methodology and Computing in Applied Probability》2004,6(1):29-53
A recent development of the Markov chain Monte Carlo (MCMC) technique is the emergence of MCMC samplers that allow transitions between different models. Such samplers make possible a range of computational tasks involving models, including model selection, model evaluation, model averaging and hypothesis testing. An example of this type of sampler is the reversible jump MCMC sampler, which is a generalization of the Metropolis–Hastings algorithm. Here, we present a new MCMC sampler of this type. The new sampler is a generalization of the Gibbs sampler, but somewhat surprisingly, it also turns out to encompass as particular cases all of the well-known MCMC samplers, including those of Metropolis, Barker, and Hastings. Moreover, the new sampler generalizes the reversible jump MCMC. It therefore appears to be a very general framework for MCMC sampling. This paper describes the new sampler and illustrates its use in three applications in Computational Biology, specifically determination of consensus sequences, phylogenetic inference and delineation of isochores via multiple change-point analysis. 相似文献
2.
本文对于突变点(Abrupt Change-Point),渐进的变点(Gradual Change-Point)和流行的变点(Epidemic Change-Point),分别给出了规范的定义,鉴于突变点问题已经有较多文献给予了讨论,本文重点讨论了后两种变点问题,给出了一些常用分布的变点的检测方法和变点的估计方法. 相似文献
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This paper presents software reliability growth models (SRGMs) with change-point based on the stochastic differential equation (SDE).Although SRGMs based on SDE have been developed in a large scale software system,considering the variation of failure distribution in the existing models during testing time is limited.These SDE SRGMs assume that failures have the same distribution.However,in practice,the fault detection rate can be affected by some factors and may be changed at certain point as time proceeds.With respect to this issue,in this paper,SDE SRGMs with changepoint are proposed to precisely reflect the variations of the failure distribution.A real data set is used to evaluate the new models.The experimental results show that the proposed models have a fairly accurate prediction capability. 相似文献
5.
研究随机设计下噪声为厚尾随机变量时非参数函数中的变点估计问题.首先,通过设计变换将随机设计转化为等间距固定设计,进而利用小波方法估计变换后的变点的位置,再利用逆设计变换求得随机设计下变点位置的估计,并给出估计的收敛速度.模拟研究结果说明对于无穷方差厚尾过程中的变点估计问题小波方法是有效的. 相似文献
6.
D. Ferger 《Acta Appl Math》2003,78(1-3):115-120
We prove a functional law of the iterated logarithm for U-statistics type processes. The result is used to determine the almost sure set of limit points for change-point estimators. 相似文献
7.
《Journal of computational and graphical statistics》2013,22(1):221-239
We propose a computational methodology to compute and extract circadian rhythmic patterns from an individual animal’s activity-event time series. This lengthy dataset, composed of a sequential event history, contains an unknown number of latent rhythmic cycles of varying duration and missing waveform information. Our computations aim at identifying the onset signature phase which individually indicates a sharp event intensity surge, where a subject-night ends and a brand new cycle’s subject-day begins, and collectively induces a linearity manifesting the individual circadian rhythmicity and information about the average period. Based on the induced linearity, the least squares criterion is employed to choose an optimal sequence of computed onset signature phases among a finite collection derived from the hierarchical factor segmentation (HFS) algorithm. The multiple levels of coding schemes in the HFS algorithm are designed to extract contrasting patterns of aggregation against sparsity of activity events along the entire temporal axis. This optimal sequence dissects the whole time series into a sequence of rhythmic cycles without model assumptions or ad hoc behavioral definitions regarding the missing waveform information. The performance of our methodology is favorably compared with two popular approaches based on the periodogram in a simulation study and in real data analyses. The computer code and data used in this article are available on the JCGS webpage. 相似文献
8.
基于C-D生产函数模型,采用改进最小二乘法检验规模报酬和结构性变点。首先,在最小二乘估计程序中加入规模报酬不变的约束,然后通过Wald统计量检验约束和无约束模型的差异性,以确定规模报酬情况。进行样本区间划分,在全样本区间和分段样本区间参数估计之后,通过Chow统计量检验参数的差异性,以确定结构性变点。以我国1980-2007年的数据为例,规模报酬是变化的,1986年和1994年均为结构性变点。 相似文献
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Henri Caussinus Faouzi Lyazrhi 《Annals of the Institute of Statistical Mathematics》1997,49(4):761-775
The problem of determining a normal linear model with possible perturbations, viz. change-points and outliers, is formulated as a problem of testing multiple hypotheses, and a Bayes invariant optimal multi-decision procedure is provided for detecting at most k (k > 1) such perturbations. The asymptotic form of the procedure is a penalized log-likelihood procedure which does not depend on the loss function nor on the prior distribution of the shifts under fairly mild assumptions. The term which penalizes too large a number of changes (or outliers) arises mainly from realistic assumptions about their occurrence. It is different from the term which appears in Akaikes or Schwarz criteria, although it is of the same order as the latter. Some concrete numerical examples are analyzed. 相似文献