1512 Submissions

[6] viXra:1512.0448 [pdf] submitted on 2015-12-26 16:50:32

Asymptotics of Univariate Extremes

Authors: J.Tiago de Oliveira
Comments: 36 Pages.

Second chapter Statistical Analysis of Extremes Pendor, Lisbon, 1997
Category: Statistics

[5] viXra:1512.0436 [pdf] submitted on 2015-12-26 12:04:44

Introduction to Statistical Analysis of Extremes

Authors: J.Tiago de Oliveira
Comments: 9 Pages. First chapter

J. Tiago de Oliveira last book followed the research started by Emil Julius Gumbel
Category: Statistics

[4] viXra:1512.0420 [pdf] replaced on 2016-09-23 03:50:26

Cooperative Parallel Particle Filters for Online Model Selection and Applications to Urban Mobility

Authors: L. Martino, J. Read, V. Elvira, F. Louzada
Comments: 30 Pages. (accepted; to appear) Digital Signal Processing

We design a sequential Monte Carlo scheme for the dual purpose of Bayesian inference and model selection. We consider the application context of urban mobility, where several modalities of transport and different measurement devices can be employed. Therefore, we address the joint problem of online tracking and detection of the current modality. For this purpose, we use interacting parallel particle filters, each one addressing a different model. They cooperate for providing a global estimator of the variable of interest and, at the same time, an approximation of the posterior density of each model given the data. The interaction occurs by a parsimonious distribution of the computational effort, with online adaptation for the number of particles of each filter according to the posterior probability of the corresponding model. The resulting scheme is simple and flexible. We have tested the novel technique in different numerical experiments with artificial and real data, which confirm the robustness of the proposed scheme.
Category: Statistics

[3] viXra:1512.0319 [pdf] submitted on 2015-12-14 09:37:41

On Almost Sure Convergence Rates for the Kernel Estimator of a Covariance Operator Under Negative Association

Authors: H. Jabbari1, M. Erfaniyan
Comments: 10 Pages.

Let fXn; n 1g be a strictly stationary sequence of negatively associated random variables, with common continuous and bounded distribution function F. We consider the estimation of the two-dimensional distribution function of (X1;Xk+1) based on kernel type estimators as well as the estimation of the covariance function of the limit empirical process induced by the sequence fXn; n 1g where k 2 IN0. Then, we derive uniform strong convergence rates for the kernel estimator of two-dimensional distribution function of (X1;Xk+1) which were not found already and do not need any conditions on the covari- ance structure of the variables. Furthermore assuming a convenient decrease rate of the covariances Cov(X1;Xn+1); n 1, we prove uniform strong convergence rate for covari- ance function of the limit empirical process based on kernel type estimators. Finally, we use a simulation study to compare the estimators of distribution function of (X1;Xk+1).
Category: Statistics

[2] viXra:1512.0294 [pdf] submitted on 2015-12-12 02:35:48

Mutual Information and Nonadditive Entropies: The Case of Tsallis Entropy

Authors: Amelia Carolina Sparavigna
Comments: 4 Pages. Published in International Journal of Sciences, 2015, 4(10):1-4. DOI:10.18483/ijSci.845

Mutual information of two random variables can be easily obtained from their Shannon entropies. However, when nonadditive entropies are involved, the calculus of the mutual information is more complex. Here we discuss the basic matter about information from Shannon entropy. Then we analyse the case of the generalized nonadditive Tsallis entropy
Category: Statistics

[1] viXra:1512.0293 [pdf] submitted on 2015-12-12 02:40:18

Relations Between Tsallis and Kaniadakis Entropic Measures and Rigorous Discussion of Conditional Kaniadakis Entropy

Authors: Amelia Carolina Sparavigna
Comments: 4 Pages. Published in International Journal of Sciences, 2015, 4(10):47-50. DOI:10.18483/ijSci.866

Tsallis and Kaniadakis entropies are generalizing the Shannon entropy and have it as their limit when their entropic indices approach specific values. Here we show some relations existing between Tsallis and Kaniadakis entropies. We will also propose a rigorous discussion of the conditional Kaniadakis entropy, deduced from these relations.
Category: Statistics