A discrete analogue of odd Weibull-G family of distributions: properties,classical and Bayesian estimation with applications to count data

In the statistical literature, several discrete distributions have been developed so far. However, in this progressive technological era, the data generated from different fields is getting complicated day by day, making it difficult to analyze this real data through the various discrete distributions available in the existing literature. In this context, we have proposed a new flexible family of discrete models named discrete odd Weibull-G (DOW-G) family. Its several impressive distributional characteristics are derived. A key feature of the proposed family is its failure rate function that can take a variety of shapes for distinct values of the unknown parameters, like decreasing, increasing, constant, J-, and bathtub-shaped. Furthermore, the presented family not only adequately captures the skewed and symmetric data sets, but it can also provide a better fit to equi-, over-, under-dispersed data. After producing the general class, two particular distributions of the DOW-G family are extensively studied. The parameters estimation of the proposed family, are explored by the method of maximum likelihood and Bayesian approach. A compact Monte Carlo simulation study is performed to assess the behavior of the estimation methods. Finally, we have explained the usefulness of the proposed family by using two different real data sets.     

Advancing OSCM scientific knowledge by replicating empirical findings: Step-by-step procedure and illustration for transformative replication endeavors

Replication endeavors contribute to the accumulation of scientific evidence about previously reported findings and are crucial for scientific progress. Replication studies are, however, often discouraged and rarely published in the operations and supply chain management (OSCM) discipline. In this article, we offer a framework for replications consisting of two complementary tables. This framework recognizes two types of replications already defined in the literature (i.e., The Exact (EXT) Replication and the Methods-Only (MTD) Replication) and adds to these two new types (i.e., the Bounded-Conceptual-Extension (BCE) Replication and the Transformative (TRF) Replication). The framework clarifies what constitutes replications, forms of replication endeavors, and their purposes. Importantly, we also differentiate replication endeavors from reproducibility tests, robustness checks, and post hoc analyses. Moreover, we describe a seven-step procedure to guide the design, execution, and presentation of replication endeavors, illustrating these steps by conducting a TRF Replication that incorporates, at the same time, a BCE Replication and an MTD Replication of Polyviou et al. (2018). The proposed framework and seven-step procedure hopefully motivate OSCM scholars to embrace replications as valuable scientific endeavors that can yield corroborating evidence to bolster confidence in previously reported findings and, better yet, provide new nuanced findings to advance precise scientific understanding of past and new OSCM phenomena.     

Reliability analysis of man–machine systems using fuzzy cognitive mapping with genetic tuning

This article offers a method for analyzing the reliability of a man–machine system (MMS) and ranking of influencing factors based on a fuzzy cognitive map (FCM). The ranking of influencing factors is analogous to the ranking of system elements the probabilistic theory of reliability. To approximate the dependence of “influencing factors—reliability,” the relationship of variable increments is used, which ensures the sensitivity of the reliability level to variations in the levels of influencing factors. The novelty of the method lies in the fact that the expert values of the weights of the FCM graph edges (arcs) are adjusted based on the results of observations using a genetic algorithm. The algorithm's chromosomes are generated from the intervals of acceptable values of edge weights, and the selection criterion is the sum of squares of deviations of the reliability simulation results from observations. The method is illustrated by the example of a multifactor analysis of the reliability of the “driver–car–road” system. It is shown that the FCM adjustment reduces the discrepancy between the reliability forecast and observations almost in half. Possible applications of the method can be complex systems with vaguely defined structures whose reliability depends very much on interrelated factors measured expertly.     

Analyzing and Modeling the Maximum Diversity Problem by Zero-One Programming*

The problem of maximizing diversity deals with selecting a set of elements from some larger collection such that the selected elements exhibit the greatest variety of characteristics. A new model is proposed in which the concept of diversity is quantifiable and measurable. A quadratic zero-one model is formulated for diversity maximization. Based upon the formulation, it is shown that the maximum diversity problem is NP-hard. Two equivalent linear integer programs are then presented that offer progressively greater computational efficiency. Another formulation is also introduced which involves a different diversity objective. An example is given to illustrate how additional considerations can be incorporated into the maximum diversity model.     

Minimizing Misclassifications in Linear Discriminant Analysis*

A procedure is developed for determining two-group linear discriminant classifiers that misclassify the fewest number of observations in the training sample. An experimental study confirms the value of this approach.     

DYNAMIC LOCATION MODELING FOR PUBLIC-SECTOR FACILITIES: A MULTICRITERIA APPROACH*

A major complication in the planning of facility systems and in the analysis of their locational configurations is the fluctuating nature of the systems they serve. Locations identified now, based on current conditions, may be undesirable in the future, and those based on future conditions may be undesirable now. This paper proposes a general methodology using multiobjective analysis to plan public-sector facility systems operating in a dynamic environment. A model is developed for the specific case of locating emergency services and an illustrative example is presented.     

隧道岩体抗力模式的随机-模糊估计方法

指出隧道结构抗力是同时含有随机性和模糊性的随机－模糊变量，提出了实用于这类变量的随机－模糊统计方法，包括随机－模糊均值和方差，以及随机－模糊概率分布的估计等。对应的传统随机方法作为一种特例被包含于其中。     

软件开发中的测试技术

在分析了软件测试重要性的基础上 ,提出了软件测试的五大原则 ,指出软件测试的内容和步骤应基于软件生命周期的全过程 ,并就测试方法、测试策略的合理选择进行了阐述。通过对测试时间、测试成本和可靠度的关系的分析 ,给出了软件最佳测试时间的确定方法 ,并对测试工作的可靠性评价进行了探讨     

Locating Emergency Warning Sirens

In this paper, we report on the application of set covering and maximal covering location models to the problem of locating emergency warning sirens in a midwestern city. Two siren types are available, each having different costs and covering radii. Using a modified version of the set covering location model, we analyze the cost implications of several policy options being considered by the city's planners. Results of the study indicate that location covering models can be powerful and efficient tools in the design of such systems, and their use can lead to significant cost savings. In addition, such models provide decision makers the flexibility to examine the inherent costs associated with various policy options.     

“Do as I Do and Not as I Say”: Exploring Price‐Oriented Maverick Buying During Supplier Selection

This article empirically examines the occurrence of price‐oriented maverick buying (MB) during supplier selection, in a direct purchasing process context. Drawing on agency theory, maverick buying, and total cost of ownership (TCO) literature, the statistically significant existence of price‐oriented MB is investigated and the purchasing manager (PM)‐related factors that influence such noncompliant behavior are determined. A discrete choice experiment is designed to simulate a TCO‐based supplier selection process in which an established purchasing framework agreement stipulates PMs not necessarily be price‐oriented (i.e., select suppliers primarily based on lowest price), and then models PM choice behavior in the supplier selection process (SSP), utilizing a conditional logit model (CLM) to determine PM compliance to the established purchasing framework agreement and identify if price‐oriented MB exists. Statistical tests utilizing comprehensive primary and secondary data are then conducted to determine if correlational relationships exist between PM‐related factors and PM price‐orientation. Results indicate that three PM‐related factors bear a significant correlational relationship to PM price‐orientation.