Geeta distribution and its properties

A new discrete distribution defined over all the positive integers and with the name of Geeta distribution is described. It is L-shaped like the logarithmic series distribution, Yule distribution and the discrete Pareto distribution but is far more versatile than them as it has two parameters. It belongs to the classes of location parameter distributions, modified power series distributions, Lagrange series distributions and exponential distributions. Its mean fi, variance a2 and two recurrence formulae for higher central moments are obtained. Convolution theorem and variations in the model with changes in the parameters have been considered. ML estimators, MVU estimators and estimators based of mean and variance and on mean and first frequency have been derived.     

On the one-sample location hypothesis for mixed bivariate data

We study a hypothesis testing problem involving the location model suggested by Olkin and Tate (1961). Specifically, we derive a likelihood ratio lest of the associated location hypothesis as an alternative to the conventional method of carrying out separate tests for each of the parameters. A small sample Monte Carlo comparison indicates the general superiority of the former in terms of statistical power. We also comment briefly on the properties of the test.     

Network learning: Episodes of interorganizational learning towards a collective performance goal

Little is known about learning processes in horizontal networks. This study focuses on networks as learning entities, i.e. learning by multiple organizations as a group, and the mechanisms involved in developing and addressing a network-level performance goal. By using a narrative approach, we gather in-depth primary data from network members to examine: how do firms engage in network learning? and, how is network learning coordinated towards a performance goal in a horizontal inter-firm network? Our findings comprise two learning episodes: ‘learning how to compete’ and ‘learning how to perform’. These episodes help us to understand network learning processes; the relationship between network learning and organizational learning; and the regulatory role a hub firm provides towards a collective performance goal.     

Building interfirm leadership: A relational identity perspective

While leadership has been recognized as an approach to facilitating network orchestration, little is known about the mechanism through which a hub firm enhances interfirm leadership. Grounded on the theory of social identity and network orchestration, we develop a framework of the enhancement of interfirm leadership, proposing that the tendency of building leadership rests on the hub firm's ability to shape the partners' relational identity. We identify three types of role-adoption that indicate seven actions a hub firm might take to establish such an identity. We suggest that the mechanism through which leadership emerges is contingent on relationship duration, dependence asymmetry, and competition intensity.     

Confidence intervals on p(y < x) for small sample sizes

When F = G^a, confidence intervals are derived and presented in graphs for p = P(Y < X), when X and Y are independent and the sample sizes are at most 25. Also, it is demonstrated via a monte carlo simulation that this is a robust procedure, when the distributions of X and Y differ by a location parameter.     

Design and implementation methodology based on Petri net formalism of flexible manufacturing systems control

This paper presents an aided design methodology of flexible manufacturing system control with a view to industrial implementation. The approach considered through a modelling phase, the a validation phase by simulation and finally a distributed implementation phase. In the modelling phase, based on the Petri net formalism, we demonstrate the hierarchical aspect which separates the part flow control and the product resource control. In addition, we emphasize generic aspects which allow us to use an object-oriented approach. These aspects and the set of modelled objects are directly used in the simulation and production phases after an automatic translation in an implementation language (ADA in our case). In consequence, the distributed location for those two phases is well facilitated from the viewpoint of the approach used.     

论东欧新马克思主义的理论定位

"东欧新马克思主义"指的是第二次世界大战后在东欧国家兴起的一种马克思主义流派,其历史大体上分为两个时期:20世纪50-70年代,东欧新马克思主义作为稳定的学术派别存在,具体地说,包括南斯拉夫实践派、布达佩斯学派以及波兰和捷克斯洛伐克等国的新马克思主义;70年代后.东欧新马克思主义者作为个体融入到西方学术界,但其学术创作仍然有着东欧新马克思主义的深刻烙印.东欧新马克思主义与通常意义上的西方马克思主义以及70年代后欧美新马克思主义共同构成了20世纪新马克思主义的基本格局,其中,东欧新马克思主义鲜明的理论特色在于:其一,对马克思思想独特的、深刻的阐述;其二,对社会主义理论与实践、历史与命运的反思和对社会主义改革的理论设计;其三,对现代性的独特的理论反思.     

高精度局域定向定位技术及其精度分析

针对目前自主局域定向定位的需求,文中提出了一种在近场模型下反向利用阵列信号处理相关理论实现阵列自身的高精度定向定位方法,仿真实验表明该方法可以有效实现阵列的高精度定向定位.进一步对该方法的定向定位精度进行了理论分析,通过仿真分析了阵列所处位置、信号源数目、阵列自身天线阵元数目以及信号源位置存在误差时对定向定位精度的影响,相关实验结论具有重要的工程应用指导意义.     

洛阳方言的方位和时间后缀

洛阳方言中有而普通话没有的方位后缀有20个、普通话里有而洛阳方言中没有的方位后缀有4个、洛阳方言与普通话都有的方位后缀有7个(包含零形式后缀);洛阳方言中有而普通话没有的时间后缀有7个、洛阳话和普通话里都有的时间后缀有6个(包含零形式后缀)。总体上讲,洛阳方言与普通话在方位和时间后缀的使用方面既有共性又有差别,差别大于共性。     

Failure Probability Under Parameter Uncertainty

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location‐scale families (including the log‐normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications.