Titlebook: Structural Changes and their Econometric Modeling; Vladik Kreinovich,Songsak Sriboonchitta Conference proceedings 2019 Springer Nature Swi

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書目名稱Structural Changes and their Econometric Modeling影響因子(影響力)




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書目名稱Structural Changes and their Econometric Modeling被引頻次學(xué)科排名




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paradigm

Algorithmic Need for Subcopulascopulas are not needed, since every subcopula can be extended to a copula. In this paper, we prove, however, that from the algorithmic viewpoint, it is, in general, not possible to always generate a copula. Thus, from the algorithmic viewpoint, subcopulas are needed.

Cantankerous

The Replacement for Hypothesis Testingified via statistical methods. The limitations and abuses of in particular p-values are so well known and by now so egregious, that a new method is badly in need. We propose returning to an old idea, making direct predictions by models of observables, assessing the value of evidence by the change in

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暴露他抗議

My Ban on Null Hypothesis Significance Testing and Confidence Intervalsth a focus on the different types of assumptions that compose the models on which .-values and confidence intervals are based. For the computation of .-values, in addition to problematic model assumptions, there also is the problem that .-values confound the implications of sample effect sizes and s

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Kalman Filter and Structural Change Revisited: An Application to Foreign Trade-Economic Growth Nexus2009 global financial crisis, oil price crash that started in 2014 as well as political uncertainties in the country. Parameters of econometric models are dependent on prevailing policy and will react to policy changes. Yet, previous researches on trade-growth modelling in Nigeria had assumed parame

GRATE

Statisticians Should Not Tell Scientists What to Thinkstatistics; that is not inappropriate. Mimetic modeling, whose goal is to mimic Nature’s behavior, is described and advocated. Both Bayesian analyses and some classical analyses may be appropriately applied to mimetic models. Statistics should not usurp scientific judgment and, in mimetic modeling,

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許可

Cumulative Residual Entropy-Based Goodness of Fit Test for Location-Scale Time Series Modelest for iid samples is introduced and the asymptotic behavior of the CRE-based GOF test and its bootstrap version is investigated for location-scale time series models. In particular, the influence of change points on the GOF test is studied through Monte Carlo simulations.

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