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61.
Genetic algorithms (GAs) are adaptive search techniques designed to find near-optimal solutions of large scale optimization problems with multiple local maxima. Standard versions of the GA are defined for objective functions which depend on a vector of binary variables. The problem of finding the maximum a posteriori (MAP) estimate of a binary image in Bayesian image analysis appears to be well suited to a GA as images have a natural binary representation and the posterior image probability is a multi-modal objective function. We use the numerical optimization problem posed in MAP image estimation as a test-bed on which to compare GAs with simulated annealing (SA), another all-purpose global optimization method. Our conclusions are that the GAs we have applied perform poorly, even after adaptation to this problem. This is somewhat unexpected, given the widespread claims of GAs' effectiveness, but it is in keeping with work by Jennison and Sheehan (1995) which suggests that GAs are not adept at handling problems involving a great many variables of roughly equal influence.We reach more positive conclusions concerning the use of the GA's crossover operation in recombining near-optimal solutions obtained by other methods. We propose a hybrid algorithm in which crossover is used to combine subsections of image reconstructions obtained using SA and we show that this algorithm is more effective and efficient than SA or a GA individually. 相似文献
62.
W. James Gauderman 《Statistics and Computing》1995,5(3):237-243
The field of genetic epidemiology is growing rapidly with the realization that many important diseases are influenced by both genetic and environmental factors. For this reason, pedigree data are becoming increasingly valuable as a means of studying patterns of disease occurrence. Analysis of pedigree data is complicated by the lack of independence among family members and by the non-random sampling schemes used to ascertain families. An additional complicating factor is the variability in age at disease onset from one person to another. In developing statistical methods for analysing pedigree data, analytic results are often intractable, making simulation studies imperative for assessing the performance of proposed methods and estimators. In this paper, an algorithm is presented for simulating disease data in pedigrees, incorporating variable age at onset and genetic and environmental effects. Computational formulas are developed in the context of a proportional hazards model and assuming single ascertainment of families, but the methods can be easily generalized to alternative models. The algorithm is computationally efficient, making multi-dataset simulation studies feasible. Numerical examples are provided to demonstrate the methods. 相似文献
63.
糯杂种高粱的9个农艺性状的相关分析表明,性状的遗传相关系数绝大多数大于表型相关系数。茎粗与千粒重相关的环境效应大,而基因型效应小,提高茎粗对增加千粒重主要靠环境效应。穗粒数与穗粒重的基因型相关和环境相关系数均大,故穗粒重的提高是基因和环境效应共同作用的结果。穗长和穗粒数与穗粒重呈正相关达显著或极显著水平,而一级分枝数和千粒重与穗粒重相关不显著。通径分析表明,穗粒数对穗粒重的直接效应最大,而穗长主要是起间接作用。从分析的4个性状来讲,对穗粒重的直接效应分别是穗粒数>株高>茎粗>穗长。 相似文献
64.
本文在贝叶斯分析的框架下讨论了面板数据的可加模型分位回归建模方法。首先通过低秩薄板惩罚样条展开和个体效应虚拟变量的引进将非参数模型转换为参数模型,然后在假定随机误差项服从非对称Laplace分布的基础上建立了贝叶斯分层分位回归模型。通过对非对称Laplace分布的分解,论文给出了所有待估参数的条件后验分布,并构造了待估参数的 Gibbs抽样估计算法。计算机模拟仿真结果显示,新提出的方法相比于传统的可加模型均值回归方法在估计稳健性上明显占优。最后以消费支出面板数据为例研究了我国农村居民收入结构对消费支出的影响,发现对于农村居民来说,无论是高、中、低消费群体,工资性收入与经营净收入的增加对其消费支出的正向刺激作用更为明显。进一步,相比于高消费农村居民人群,低消费农村居民人群随着收入的增加消费支出上升速度较为缓慢。 相似文献
65.
Recently, there has been a lot of interest in group technology (GT) from researchers as well as from practitioners. This interest is explained by the fact that GT supports new manufacturing philosophies. One of the main issues in GT is the part family formation problem which is concerned with grouping similar products into same families. Many researchers have tackled this problem and many algorithms have been proposed for it. In this paper, we present a genetic technique-based heuristic for the quadratic integer programming model of the part family formation problem which was formulated by Kusiak et al. (1986). The heuristic is tested on several problems from the literature, and preliminary results are very promising. 相似文献
66.
Josef Schürle 《Statistical Papers》2005,46(3):433-449
An objective of Record Linkage is to link two data files by identifying common elements. A popular model for doing the separation
is the probabilistic one from Fellegi and Sunter. To estimate the parameters needed for the model usually a mixture model
is constructed and the EM algorithm is applied. For simplification, the assumption of conditional independence is often made.
This assumption says that if several attributes of elements in the data are compared, then the results of the comparisons
regarding the several attributes are independent within the mixture classes. A mixture model constructed with this assumption
has been often used. Within this article a straightforward extension of the model is introduced which allows for conditional
dependencies but is heavily dependent on the choice of the starting value. Therefore also an estimation procedure for the
EM algorithm starting value is proposed. The two models are compared empirically in a simulation study based on telephone
book entries. Particularly the effect of different starting values and conditional dependencies on the matching results is
investigated. 相似文献
67.
《Journal of Statistical Computation and Simulation》2012,82(8):599-611
In this paper the use of the empirical Fisher information matrix as an estimator of the information matrix is considered in the context of response models and incomplete data problems. The introduction of an additional stochastic component into such models is shown to greatly increase the range of situations in which the estimator can be employed. In particular the conditions for its use in incomplete data problems are shown to be the same as those needed to justify the use of the EM algorithm. 相似文献
68.
Many areas of statistical modeling are plagued by the “curse of dimensionality,” in which there are more variables than observations. This is especially true when developing functional regression models where the independent dataset is some type of spectral decomposition, such as data from near-infrared spectroscopy. While we could develop a very complex model by simply taking enough samples (such that n > p), this could prove impossible or prohibitively expensive. In addition, a regression model developed like this could turn out to be highly inefficient, as spectral data usually exhibit high multicollinearity. In this article, we propose a two-part algorithm for selecting an effective and efficient functional regression model. Our algorithm begins by evaluating a subset of discrete wavelet transformations, allowing for variation in both wavelet and filter number. Next, we perform an intermediate processing step to remove variables with low correlation to the response data. Finally, we use the genetic algorithm to perform a stochastic search through the subset regression model space, driven by an information-theoretic objective function. We allow our algorithm to develop the regression model for each response variable independently, so as to optimally model each variable. We demonstrate our method on the familiar biscuit dough dataset, which has been used in a similar context by several researchers. Our results demonstrate both the flexibility and the power of our algorithm. For each response variable, a different subset model is selected, and different wavelet transformations are used. The models developed by our algorithm show an improvement, as measured by lower mean error, over results in the published literature. 相似文献
69.
本文运用可信性理论建立了模糊需求条件下新产品供应链配置的模糊机会约束规划模型,对模型的求解进行了分析,并用遗传算法进行求解。算例分析表明,运用本文提出的方法可以从供应商的选择、阶段库存和客户服务水平三个方面对模糊需求条件下的新产品供应链进行配置优化。 相似文献
70.