Statistics

2102 Submissions

[3] viXra:2102.0094 [pdf] submitted on 2021-02-17 23:44:54

The kth Power Expectile Estimation and Testing

Authors: Fuming Lin, Yingying Jiang, Yong Zhou
Comments: 57 Pages.

This paper develops the theory of the kth power expectile estimation and considers its relevant hypothesis tests for coefficients of linear regression models. We prove that the asymptotic covariance matrix of kth power expectile regression converges to that of quantile regression as k converges to one, and hence provide a moment estimator of asymptotic matrix of quantile regression. The kth power expectile regression is then utilized to test for homoskedasticity and conditional symmetry of the data. Detailed comparisons of the local power among the kth power expectile regression tests, the quantile regression test, and the expectile regression test have been provided. When the underlying distribution is not standard normal, results show that the optimal k are often larger than 1 and smaller than 2, which suggests the general kth power expectile regression is necessary.
Category: Statistics

[2] viXra:2102.0027 [pdf] submitted on 2021-02-05 13:05:30

Hamiltonian Markov Chain Monte Carlo Using Second Derivatives

Authors: Stephen P. Smith
Comments: 10 Pages.

Hamiltonian Markov Chain Monte Carlo is one of the established methods to conduct a Bayesian simulation. This method uses evaluations of the probability density and its gradient at particular variables. This present paper describes how to incorporate information from second derivatives that relate to a direction set, and describes how to modify the simulation accordingly.
Category: Statistics

[1] viXra:2102.0026 [pdf] submitted on 2021-02-05 22:05:06

Revisiting the UK EU Membership Referendum (Brexit) Poll Tracker

Authors: Michaelino Mervisiano
Comments: 37 Pages. [Corrections made by viXra Admin to conform with the requirements on the Submission Form]

On the 23rd June 2016, the United Kingdom (UK) European Union (EU) membership referendum resulted in 51.9% of voters voted to leave EU—popularly termed as Brexit. Given its significant implications, correctly predicting Brexit was crucial but most pollsters predicted incorrectly. This paper assesses whether Brexit was evident and predictable from the pre-referendum polls data. Unlike previous studies—whose analytical tools are limited to latest poll analysis, descriptive statistics, point estimate, and simple linear regression—this project use more robust and sophisticated statistical methodologies
Category: Statistics