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In the literature, assuming independence of random variables X and Y, statistical estimation of the stress–strength parameter R = P(X > Y) is intensively investigated. However, in some real applications, the strength variable X could be highly dependent on the stress variable Y. In this paper, unlike the common practice in the literature, we discuss on estimation of the parameter R where more realistically X and Y are dependent random variables distributed as bivariate Rayleigh model. We derive the Bayes estimates and highest posterior density credible intervals of the parameters using suitable priors on the parameters. Because there are not closed forms for the Bayes estimates, we will use an approximation based on Laplace method and a Markov Chain Monte Carlo technique to obtain the Bayes estimate of R and unknown parameters. Finally, simulation studies are conducted in order to evaluate the performances of the proposed estimators and analysis of two data sets are provided. 相似文献
73.
In this paper it is investigated whether the positive effect of mothers' education on child survival is similar for boys and girls in Matlab, Bangladesh. The study is based on follow-up of 7,913 live births that occurred in the study area during the whole of 1982. The five independent variables included in the analysis are: sex of children, mother's education, mother's age at the time of birth, household economic condition, and health programme block. Hazard analysis shows that the positive effect of mother's education on child survival is different for boys and girls. For boys, a change in mother's education from no schooling to 1–5 years resulted in reducing the predicted risk of death by 45 per cent, while for the girls the reduction came to only seven per cent. Similarly, a change in mother's education from no schooling to six or more years of schooling resulted in a reduction of risk of 70 per cent for boys, while for girls it was only 32 per cent. 相似文献
74.
In numerous situations, we use ranks dataset to exhibit preferences of a group of respondents towards a set of items. While assigning ranks, judges may consider several factors contributing to overall ranks of items. In this study, an attempt is made to model factors influencing the judges’ evaluations of items through mixture models for preference datasets. Both the probabilistic features of the mixture distribution and inferential as well as computational issues emerging out of the maximum likelihood estimation are addressed. Moreover, empirical evidences from observed dataset confirming the plausibility of the proposed model to preference dataset are provided. 相似文献
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Although terrorism has been widely studied for its impact and potential determinants in Pakistan, the answer to the policy question regarding the role of external factors in influencing specifically the sectarian terrorism is not empirically well researched. The study, particularly, analyses the role of Pakistan’s regional foreign policy towards neighbouring India, Afghan wars, and the relations with bi-polar fundamental Muslim Block, the Kingdom of Saudi Arabia (KSA) and Iran, on sectarian (religious) terrorist incidents for the period 1973–2017. The findings suggest that economic cooperation with India which drive peace-making relations increases the sectarian terrorism. Both the bilateral loans disbursed by the KSA and trade relations with Iran, significantly increase the chances of sectarian terrorism in Pakistan by activating extremist (proxy) groups. However, the Afghan Wars that call for Pak-US strategic partnership helps Pakistan to control the religious terrorism. 相似文献
77.
Amiri Mehdi Balakrishnan Narayanaswamy Eftekharian Abbas 《Statistical Methods and Applications》2022,31(3):679-707
Statistical Methods & Applications - In this paper, some stochastic comparison results are developed for the class of multivariate normal variance-mean mixture (NVM) distributions. These... 相似文献