Normal mean-variance Lindley Birnbaum-Saunders distribution

The generalization of Birnbaum-Saunders (BS) distribution has recently received considerable attention to provide accurate inferential results in dealing with survival data, reliability problems, fatigue life studies and hydrological data. This paper introduces a new extension of the BS distribution based on the normal mean-variance mixture of Lindley distribution. Since the proposed lifetime distribution can take positive and negative skewness and can have decreasing, increasing, upside-down bathtub, increasing-decreasingincreasing and decreasing-increasing-decreasing hazard rate functions, it may provide more flexible model than the existing extensions of BS distribution. Some properties of the new distribution are derived and the computationally analytical EM-type algorithm is developed for computing maximum likelihood estimates. Finally, the performance of the proposed methodology is illustrated through analyzing two real data sets.https://www.intlpress.com/site/pub/pages/journals/items/sii/_home/_main/index.phppm2020Statistic

A theoretical framework for Landsat data modeling based on the matrix variate mean-mixture of normal model

This paper introduces a new family of matrix variate distributions based on the mean-mixture of normal (MMN) models. The properties of the new matrix variate family, namely stochastic representation, moments and characteristic function, linear and quadratic forms as well as marginal and conditional distributions are investigated. Three special cases including the restricted skew-normal, exponentiated MMN and the mixed-Weibull MMN matrix variate distributions are presented and studied. Based on the specific presentation of the proposed model, an EM-type algorithm can be directly implemented for obtaining maximum likelihood estimate of the parameters. The usefulness and practical utility of the proposed methodology are illustrated through two conducted simulation studies and through the Landsat satellite dataset analysis.The National Research Foundation (NRF) of South Africa and STATOMET.http://www.plosone.orgam2021Statistic

Effect of opium consumption on cardiovascular diseases � a cross- sectional study based on data of Rafsanjan cohort study

Background: There are differences of opinion about the beneficial or detrimental effects of opium consumption on cardiovascular diseases (CVDs). So, we aimed to study the association between opium use and CVDs. Methods: We used data obtained from the Rafsanjan Cohort Study (RCS), as a part of the prospective epidemiological research studies in IrAN (PERSIAN), with detailed, validated data on opium consumption and some other exposures. A total of 10,000 adults were enrolled in the study. Logistic regression models were used to assess the possible relationships of opium consumption with the prevalence of ischemic heart diseases (IHD) and myocardial infarction (MI). Results: In this study, 9990 participants in the baseline phase of the Rafsanjan adult cohort study were included according to their completed questionnaire. Among all participants, 870 and 296 individuals were found to suffer from IHD and MI, respectively. Opium consumption was found to be relatively high in the RCS participants, especially in men (men = 2150 and women = 228). Opium use was associated with a higher odds of IHD and MI, with the adjusted odds ratios (95 CI) of 1.51 (1.22�1.86) and 1.79 (1.31�2.45), respectively. Also, dose-response increases were observed with the highest odds ratios in the 4th quartile for MI and IHD (p-values for trend < 0.001). Increased odds were observed for the two main methods of opium consumption, i.e. oral and smoking, but oral administration had higher odds ratio. Conclusions: Opium consumption is associated with the increased odds of both IHD and MI diseases. © 2021, The Author(s)

Proximity curves for potential-based clustering

YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

Merits of Industrial Clustering: Case of Date’s Industry of Iran

Significance of industrial development made many countries consider the formation and strengthening of small and medium industries of industrial fields, in form of cluster as regional industrial development strategy, and utilize it as employment strategy which is able to improve competition abilities of enterprises and so to enhance their export potentials. Above 90 percent of Iran industries are formed by small and medium enterprises, and based on identified properties of industrial clusters in different regions, cluster development is one of the appropriate and effective patterns for business expansion. Considering the importance of date production in Iran, can be said that development of date industrial cluster has a lot of positive impacts in economic, industrial, social and environmental fields. In this study, by using the technique of DEMATEL, 7 major effective criteria on operation of date industrial cluster including 4 operational features, and 3 sufficiency features were recognized and extracted under supervision of the experts and based on the most practical choices which are compatible with the environment of practical structures of industrial clusters. Results of this research show that networking feature has its priority among practical criteria, export feature includes a high influence taking rate, and feature of cluster enterprises has the most effectiveness and interaction with the other studied criteria. This study indicates that using partnership and networking approach is one of the appropriate ways to solve problems of clusters and is operational for other local and regional clusters