Statistical distributions play a prominent role for modeling data in applied fields, particularly in actuarial, financial sciences, and risk management fields. Among the statistical distributions, the heavy-tailed distributions have proven the best choice to use for modeling heavy-tailed financial data. The actuaries are often in search of such types of distributions to provide the best description of the actuarial and financial data. This study presents a new power transformation to introduce a new family of heavy-tailed distributions useful for modeling heavy-tailed (...) financial data. A submodel, namely, heavy-tailed beta-power transformed Weibull model is considered to demonstrate the adequacy of the proposed method. Some actuarial measures such as value at risk, tail value at risk, tail variance, and tail variance premium are calculated. A brief simulation study based on these measures is provided. Finally, an application to the insurance loss dataset is analyzed, which revealed that the proposed distribution is a superior model among the competitors and could potentially be very adequate in describing and modeling actuarial and financial data. (shrink)

This paper introduces the new novel four-parameter Weibull distribution named as the Marshall–Olkin alpha power Weibull distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation, maximum product spacing, and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model’s supremacy upon some famous distributions is explained using two real data sets (...) and it is shown that the MOAPW model can achieve better fits than other competitive distributions. (shrink)

Modelling data in applied areas particularly in reliability engineering is a prominent research topic. Statistical models play a vital role in modelling reliability data and are useful for further decision-making policies. In this paper, we study a new class of distributions with one additional shape parameter, called a new generalized exponential-X family. Some of its properties are taken into account. The maximum likelihood approach is adopted to obtain the estimates of the model parameters. For assessing the performance of these estimators, (...) a comprehensive Monte Carlo simulation study is carried out. The usefulness of the proposed family is demonstrated by means of a real-life application representing the failure times of electronic components. The fitted results show that the new generalized exponential-X family provides a close fit to data. Finally, considering the failure times data, the Bayesian analysis and performance of Gibbs sampling are discussed. The diagnostics measures such as the Raftery–Lewis, Geweke, and Gelman–Rubin are applied to check the convergence of the algorithm. (shrink)

The problem of finding optimal sampling schemes has been resolved in two models. The novelty of this study lies in its cost efficiency, specifically, for the applied problems with expensive sampling process. In discussed models, we show that some observations counteract other ones in prediction mechanism. The autocovariance function of underlying process causes mentioned result. Our interesting result is that, although removing neutralizing observations convert sampling scheme to nonredundant case, it causes to worse prediction. A simulation study confirms this matter, (...) too. (shrink)

This paper is concerned with the estimation of the Weibull generalized exponential distribution parameters based on the adaptive Type-II progressive censored sample. Maximum likelihood estimation, maximum product spacing, and Bayesian estimation based on Markov chain Monte Carlo methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the (...) distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice. (shrink)

This volume collects contributions from leading scholars of early modern philosophy from a wide variety of philosophical and geographic backgrounds. The distinguished contributors offer very different, competing approaches to the history of philosophy.

The introduction explain the need for how an international, inclusive discussion about the range of different methodological approaches from different traditions of philosophy can be read alongside each other and be seen in sometimes very critical conversation with each other. In addition, the introduction identifies four broad themes in the volume: the largest group of chapters advocate methods that promote history of philosophy as an unapologetic, autonomous enterprise with its own criteria within philosophy. Second, three chapters can be seen as (...) historicizing the history of philosophy from within. Third, four chapters argue for history of philosophy as a means toward making contributions to contemporary philosophy. Finally, two chapters explore the relationship between the history of philosophy and the history of science. (shrink)

The research ethics committee is a key element of university administration and has gained increasing importance as a review mechanism for those institutions that wish to conduct responsible...

This article proposes a geostatistical solution for area-to-point spatial prediction (downscaling) taking into account boundary effects. Such effects are often poorly considered in downscaling, even though they often have significant impact on the results. The geostatistical approach proposed in this article considers two types of boundary conditions (BC), that is, a Dirichlet-type condition and a Neumann-type condition, while satisfying several critical issues in downscaling: the coherence of predictions, the explicit consideration of support differences, and the assessment of uncertainty regarding the (...) point predictions. An updating algorithm is used to reduce the computational cost of area-to-point prediction under a given BC. In a case study, area-to-point prediction under a Dirichlet-type BC and a Neumann-type BC is illustrated using simulated data, and the resulting predictions and error variances are compared with those obtained without considering such conditions. (shrink)

To the historian of art, it is evident that the two authors’ notion of ‘art’ is of very recent date, and not shared by everybody. They claim: ‘The purpose of art, surely, is not merely to depict or represent reality -- for that can be accomplished very easily with a camera -- but to enhance, transcend, or even to distort reality’ . They do not explain how one could photograph Paradise or Hell, the Creation of the World, the Passion of (...) Christ, or the escapades of the ancient gods -- all subjects that can be found represented in our museums. Nor is it more legitimate to generalize from certain Indian conventions of representing the female nude than it is for the academic tradition to take the Venus de Medici for the same purpose. Even a fleeting visit to one of the great museums might serve to convince the authors that few of the exhibits conform to the laws of art they postulate. [followed by response from V.S. Ramachandran]. (shrink)

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