全文获取类型
收费全文 | 7312篇 |
免费 | 166篇 |
国内免费 | 91篇 |
专业分类
管理学 | 571篇 |
劳动科学 | 1篇 |
民族学 | 39篇 |
人才学 | 4篇 |
人口学 | 76篇 |
丛书文集 | 658篇 |
理论方法论 | 190篇 |
综合类 | 5014篇 |
社会学 | 324篇 |
统计学 | 692篇 |
出版年
2024年 | 11篇 |
2023年 | 44篇 |
2022年 | 50篇 |
2021年 | 77篇 |
2020年 | 105篇 |
2019年 | 111篇 |
2018年 | 122篇 |
2017年 | 179篇 |
2016年 | 142篇 |
2015年 | 180篇 |
2014年 | 363篇 |
2013年 | 639篇 |
2012年 | 419篇 |
2011年 | 470篇 |
2010年 | 367篇 |
2009年 | 381篇 |
2008年 | 432篇 |
2007年 | 469篇 |
2006年 | 489篇 |
2005年 | 514篇 |
2004年 | 418篇 |
2003年 | 431篇 |
2002年 | 279篇 |
2001年 | 265篇 |
2000年 | 181篇 |
1999年 | 94篇 |
1998年 | 55篇 |
1997年 | 45篇 |
1996年 | 46篇 |
1995年 | 40篇 |
1994年 | 35篇 |
1993年 | 22篇 |
1992年 | 26篇 |
1991年 | 18篇 |
1990年 | 13篇 |
1989年 | 15篇 |
1988年 | 8篇 |
1987年 | 5篇 |
1986年 | 3篇 |
1985年 | 2篇 |
1984年 | 1篇 |
1983年 | 1篇 |
1982年 | 1篇 |
1979年 | 1篇 |
排序方式: 共有7569条查询结果,搜索用时 0 毫秒
991.
A multivariate extension of the adaptive exponentially weighted moving average (AEWMA) control chart is proposed. The new multivariate scheme can detect small and large shifts in the process mean vector effectively. The proposed scheme can be viewed as a smooth combination of a multivariate exponentially weighted moving average (MEWMA) chart and a Shewhart χ2-chart. The optimal design of the proposed chart is given according to a pre-specified in-control average run length and two shift sizes; a small and large shift each measured in terms of the non centrality parameter. The signal resistance of the newly proposed multivariate chart is also given. Comparisons among the new chart, the MEWMA chart, and the combined Shewhart-MEWMA (S-MEWMA) chart in terms of the standard and worst-case average run length profiles are presented. In addition, the three charts are compared with respect to their worst-case signal resistance values. The proposed chart gives somewhat better worst-case ARL and signal resistance values than the competing charts. It also gives better standard ARL performance especially for moderate and large shifts. The effectiveness of our proposed chart is illustrated through an example with simulated data set. 相似文献
992.
In statistical process control applications, the multivariate T 2 control chart based on Hotelling's T 2 statistic is useful for detecting the presence of special causes of variation. In particular, use of the T 2 statistic based on the successive differences covariance matrix estimator has been shown to be very effective in detecting the presence of a sustained step or ramp shift in the mean vector. However, the exact distribution of this statistic is unknown. In this article, we derive the maximum value of the T 2 statistic based on the successive differences covariance matrix estimator. This distributional property is crucial for calculating an approximate upper control limit of a T 2 control chart based on successive differences, as described in Williams et al. (2006). 相似文献
993.
Wilks’ ratio statistic can be defined in terms of the ratio of the sample generalized variances of two non-independent estimators of the same covariance matrix. Recently this statistic has been proposed as a control statistic for monitoring changes in the covariance matrix of a multivariate normal process in a Phase II situation, particularly when the dimension is larger than the sample size. In this article we derive a technique for decomposing Wilks’ ratio statistic into the product of independent factors that can be associated with the components of the covariance matrix. With these results, we demonstrate that, when a signal is detected in a control procedure for the Phase II monitoring of process variability using the ratio statistic, the signaling value can be decomposed and the process variables contributing to the signal can be specifically identified. 相似文献
994.
In this article, we introduce a new distribution-free Shewhart-type control chart that takes into account the location of a single order statistic of the test sample (such as the median) as well as the number of observations in that test sample that lie between the control limits. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of the chart is that, due to its nonparametric nature, the false alarm rate and in-control run length distribution are the same for all continuous process distributions, and so will be naturally robust. Tables are provided for the implementation of the chart for some typical ARL values and false alarm rates. The empirical study carried out reveals that the new chart is preferable from a robustness point of view in comparison to a classical Shewhart-type chart and also the nonparametric chart of Chakraborti et al. (2004). 相似文献
995.
996.
Sang-Ho Lee 《统计学通讯:理论与方法》2013,42(19):3492-3503
A new control scheme is proposed by borrowing the idea of the Benjamini–Hochberg procedure for controlling the false discovery rate in multiple testing. It is shown theoretically that the proposed 2-span control scheme outperforms the Shewhart X-bar chart in terms of the average run length under any size of mean shifts. Some simulations are carried out to demonstrate that the proposed scheme having various span sizes always outperforms the X-bar chart in terms of the average run lengths. 相似文献
997.
In this paper, we propose new estimation techniques in connection with the system of S-distributions. Besides “exact” maximum likelihood (ML), we propose simulated ML and a characteristic function-based procedure. The “exact” and simulated likelihoods can be used to provide numerical, MCMC-based Bayesian inferences. 相似文献
998.
999.
AbstractIn this paper, we introduce a version of Hayter and Tsui's statistical test with double sampling for the vector mean of a population under multivariate normal assumption. A study showed that this new test was more or as efficient than the well-known Hotelling's T2 with double sampling. Some nice features of Hayter and Tsui's test are its simplicity of implementation and its capability of identifying the errant variables when the null hypothesis is rejected. Taking that into consideration, a new control chart called HTDS is also introduced as a tool to monitor multivariate process vector mean when using double sampling. 相似文献
1000.