Inference for an exponentiated Pareto record values based on the pivotal quantity

2019 ◽  
Vol 30 (4) ◽  
pp. 885-893
Author(s):  
Jung-In Seo
Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1678
Author(s):  
Jeongwook Lee ◽  
Joon Jin Song ◽  
Yongku Kim ◽  
Jung In Seo

Recently, the area of sea ice is rapidly decreasing due to global warming, and since the Arctic sea ice has a great impact on climate change, interest in this is increasing very much all over the world. In fact, the area of sea ice reached a record low in September 2012 after satellite observations began in late 1979. In addition, in early 2018, the glacier on the northern coast of Greenland began to collapse. If we are interested in record values of sea ice area, modeling relationships of these values and predicting future record values can be a very important issue because the record values that consist of larger or smaller values than the preceding observations are very closely related to each other. The relationship between the record values can be modeled based on the pivotal quantity and canonical and drawable vine copulas, and the relationship is called a dependence structure. In addition, predictions for future record values can be solved in a very concise way based on the pivotal quantity. To accomplish that, this article proposes an approach to model the dependence structure between record values based on the canonical and drawable vine. To do this, unknown parameters of a probability distribution need to be estimated first, and the pivotal-based method is provided. In the pivotal-based estimation, a new algorithm to deal with a nuisance parameter is proposed. This method allows one to reduce computational complexity when constructing exact confidence intervals of functions with unknown parameters. This method not only reduces computational complexity when constructing exact confidence intervals of functions with unknown parameters, but is also very useful for obtaining the replicated data needed to model the dependence structure based on canonical and drawable vine. In addition, prediction methods for future record values are proposed with the pivotal quantity, and we compared them with a time series forecasting method in real data analysis. The validity of the proposed methods was examined through Monte Carlo simulations and analysis for Arctic sea ice data.


2020 ◽  
Vol 8 (1) ◽  
pp. 22-35
Author(s):  
M. Shakil ◽  
M. Ahsanullah

AbstractThe objective of this paper is to characterize the distribution of the condition number of a complex Gaussian matrix. Several new distributional properties of the distribution of the condition number of a complex Gaussian matrix are given. Based on such distributional properties, some characterizations of the distribution are given by truncated moment, order statistics and upper record values.


2020 ◽  
Vol 70 (6) ◽  
pp. 1457-1468
Author(s):  
Haroon M. Barakat ◽  
M. H. Harpy

AbstractIn this paper, we investigate the asymptotic behavior of the multivariate record values by using the Reduced Ordering Principle (R-ordering). Necessary and sufficient conditions for weak convergence of the multivariate record values based on sup-norm are determined. Some illustrative examples are given.


2020 ◽  
Vol 72 (2) ◽  
pp. 89-110
Author(s):  
Manoj Chacko ◽  
Shiny Mathew

In this article, the estimation of [Formula: see text] is considered when [Formula: see text] and [Formula: see text] are two independent generalized Pareto distributions. The maximum likelihood estimators and Bayes estimators of [Formula: see text] are obtained based on record values. The Asymptotic distributions are also obtained together with the corresponding confidence interval of [Formula: see text]. AMS 2000 subject classification: 90B25


Author(s):  
Peihan Xiong ◽  
Weiwei Zhuang ◽  
Guoxin Qiu
Keyword(s):  

Author(s):  
Vladimir Kresin ◽  
Sergei Ovchinnikov ◽  
Stuart Wolf

For the past almost fifty years, scientists have been trying to explain the phenomenon of superconductivity. The mechanism is the key ingredient of microscopic theory, which was developed by Bardeen, Cooper, and Schrieffer in 1957. The theory also introduced the basic concepts of pairing, coherence length, energy gap, and so on. Since then, microscopic theory has undergone an intensive development. This book provides a very detailed theoretical treatment of the key mechanisms of superconductivity, including the current state of the art (phonons, magnons, plasmons). In addition, the book contains descriptions of the properties of the key superconducting compounds that are of the most interest for science and applications. For many years, there has been a search for new materials with higher values of the main parameters, such as the critical temperature and critical current. At present, the possibility of observing superconductivity at room temperature has become perfectly realistic. That is why the book is especially concerned with high-Tc systems such as high-Tc oxides, hydrides with record values for critical temperature under high pressure, nanoclusters, and so on. A number of interesting novel superconducting systems have been discovered recently, including topological materials, interface systems, and intercalated graphene. The book contains rigorous derivations based on statistical mechanics and many-body theory. The book also provides qualitative explanations of the main concepts and results. This makes the book accessible and interesting for a broad audience.


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