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Statistical inference of complex systems

Grant number: 17/25971-0
Support Opportunities:Scholarships in Brazil - Post-Doctorate
Effective date (Start): November 01, 2018
Effective date (End): October 31, 2021
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Francisco Aparecido Rodrigues
Grantee:Pedro Luiz Ramos
Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID

Abstract

The purpose of this post-doctoral project is to propose different estimation methods that can be applied in complex networks. Firstly, we will consider Bayesian methods to determine the minimum size of networks so that real network properties are observed as well as the distribution of the number of connections. This study will solve a fundamental problem in networks which are related to the construction of a taxonomy of complex networks. In this case, we will able to determine the main similarities and differences between classes of networks such as social and biological. Another important problem in complex systems is related to the use of power law distributions. The parameter estimators of such distributions have been discussed earlier under the maximum likelihood estimators. However, different estimation procedures, as well as, Bayesian methods may return better estimates, especially for small samples. Therefore, we will develop new tools to obtain the parameter estimates of power law distributions. In this project, we will also explore regression methods to quantify the relationship between the dynamic structure of complex networks. The aim is to quantify how local properties of the vertices can be used to predict dynamic properties, such as the oscillator synchronization level. In this case, the challenge lies in the fact that the observations are not independent and, therefore, sophisticated Bayesian methods need be considered, for instance, models using a regression structure with coupling functions. Finally, we will introduce a new estimation procedure based on a modification of the maximum likelihood estimators that allow us to obtain closed-form estimators. For this new method, sufficient and necessary conditions will be studied to obtain its asymptotic properties. (AU)

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Scientific publications (21)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
NASCIMENTO, DIEGO C.; BARBOSA, BRUNO; PEREZ, ANDRE M.; CAIRES, DANIEL O.; HIRAMA, EDGAR; RAMOS, PEDRO L.; LOUZADA, FRANCISCO. Risk Management in E-Commerce-A Fraud Study Case Using Acoustic Analysis through Its Complexity. Entropy, v. 21, n. 11, . (17/25971-0)
MORITA, LIA H. M.; TOMAZELLA, VERA L.; BALAKRISHNAN, NARAYANASWAMY; RAMOS, PEDRO L.; FERREIRA, PAULO H.; LOUZADA, FRANCISCO. Inverse Gaussian process model with frailty term in reliability analysis. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, v. 37, n. 2, p. 763-784, . (17/25971-0, 13/07375-0)
CHESNEAU, CHRISTOPHE; BAKOUCH, HASSAN S.; RAMOS, PEDRO L.; LOUZADA, FRANCISCO. The polynomial-exponential distribution: a continuous probability model allowing for occurrence of zero values. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, . (17/25971-0)
RAMOS, PEDRO L.; LOUZADA, FRANCISCO; RAMOS, EDUARDO; DEY, SANKU. The Frechet distribution: Estimation and application-An overview. JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS, . (17/25971-0)
FERREIRA, PAULO H.; RAMOS, EDUARDO; RAMOS, PEDRO L.; GONZALES, JHON F. B.; TOMAZELLA, VERA L. D.; EHLERS, RICARDO S.; SILVA, EVELINY B.; LOUZADA, FRANCISCO. Objective Bayesian analysis for the Lomax distribution. Statistics & Probability Letters, v. 159, . (17/25971-0)
DO NASCIMENTO, DIEGO CARVALHO; RAMOS, PEDRO LUIZ; ELAL-OLIVERO, DAVID; CORTES-ARAYA, MILTON; LOUZADA, FRANCISCO. Generalizing Normality: Different Estimation Methods for Skewed Information. SYMMETRY-BASEL, v. 13, n. 6, . (13/07375-0, 20/09174-5, 17/25971-0)
RAMOS, PEDRO L.; ALMEIDA, MARCO P.; TOMAZELLA, VERA L. D.; LOUZADA, FRANCISCO. Improved Bayes estimators and prediction for the Wilson-Hilferty distribution. Anais da Academia Brasileira de Ciências, v. 91, n. 3, . (17/25971-0)
RAMOS, PEDRO L.; DEY, DIPAK K.; LOUZADA, FRANCISCO; LACHOS, VICTOR H.. An extended poisson family of life distribution: a unified approach in competitive and complementary risks. Journal of Applied Statistics, v. 47, n. 2, . (17/25971-0)
RAMOS, PEDRO L.; DEY, DIPAK K.; LOUZADA, FRANCISCO; RAMOS, EDUARDO. On Posterior Properties of the Two Parameter Gamma Family of Distributions. Anais da Academia Brasileira de Ciências, v. 93, n. 3, . (17/25971-0, 19/27636-9, 13/07375-0)
MORITA, LIA H. M.; TOMAZELLA, VERA L.; FERREIRA, PAULO H.; RAMOS, PEDRO L.; BALAKRISHNAN, NARAYANASWAMY; LOUZADA, FRANCISCO. Optimal burn-in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, v. 37, n. 3, SI, p. 612-627, . (13/07375-0, 17/25971-0)
RAMOS, P. L.; COSTA, L. F.; LOUZADA, F.; RODRIGUES, F. A.. Power laws in the Roman Empire: a survival analysis. ROYAL SOCIETY OPEN SCIENCE, v. 8, n. 7, . (15/22308-2, 13/07375-0, 17/25971-0)
MORITA, LIA H. M.; TOMAZELLA, VERA L. D.; RAMOS, PEDRO L.; FERREIRA, PAULO H.; LOUZADA, FRANCISCO. The random deterioration rate model with measurement error based on the inverse Gaussian distribution. BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS, v. 35, n. 1, p. 187-204, . (17/25971-0)
RAMOS, PEDRO LUIZ; LOUZADA, FRANCISCO. A note on the exponential geometric power series distribution. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, . (17/25971-0)
TOMAZELLA, VERA L. D.; DE JESUS, SANDRA R.; LOUZADA, FRANCISCO; NADARAJAH, SARALEES; RAMOS, PEDRO L.. Reference Bayesian analysis for the generalized lognormal distribution with application to survival data. STATISTICS AND ITS INTERFACE, v. 13, n. 1, p. 139-149, . (17/25971-0)
P. L. RAMOS; D. C. NASCIMENTO; R. FERNANDES; E. GUIMARÃES; M. SANTANA; K. SOARES; F. LOUZADA. Medical Care in Emergency Units with Risk Classification: Time to Attendance at a Hospital based on Parametric Models. TEMA (São Carlos), v. 20, n. 3, p. 571-585, . (17/25971-0)
SABOOR, ABDUS; KHAN, MUHAMMAD NAUMAN; CORDEIRO, GAUSS M.; PASCOA, MARCELINO A. R.; RAMOS, PEDRO L.; KAMAL, MUSTAFA. Some new results for the transmuted generalized gamma distribution. Journal of Computational and Applied Mathematics, v. 352, p. 165-180, . (17/25971-0)
TOMAZELLA, VERA LUCIA DAMASCENO; JESUS, SANDRA REGO; GAZON, AMANDA BUOSI; LOUZADA, FRANCISCO; NADARAJAH, SARALEES; NASCIMENTO, DIEGO CARVALHO; RODRIGUES, FRANCISCO APARECIDO; RAMOS, PEDRO LUIZ. Bayesian Reference Analysis for the Generalized Normal Linear Regression Model. SYMMETRY-BASEL, v. 13, n. 5, . (20/09174-5, 13/07375-0, 17/25971-0)
DE ALMEIDA, MARCELLO HENRIQUE; RAMOS, PEDRO LUIZ; RAO, GADDE SRINIVASA; MOALA, FERNANDO ANTONIO. Objective Bayesian inference for the capability index of the Gamma distribution. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, v. 37, n. 5, p. 2235-2247, . (17/25971-0)
DIEGO CARVALHO DO NASCIMENTO; PEDRO LUIZ RAMOS; ANDRÉ ENNES; CAMILA COCOLO; MÁRCIO JOSÉ NICOLA; CARLOS ALONSO; LUIZ GUSTAVO RIBEIRO; FRANCISCO LOUZADA. Um estudo de caso de engenharia de confiabilidade de colhedoras de cana-de-açúcar. Gestão & Produção, v. 27, n. 4, . (17/25971-0)
MORITA, LIA H. M.; TOMAZELLA, VERA L.; FERREIRA, PAULO H.; RAMOS, PEDRO L.; BALAKRISHNAN, NARAYANASWAMY; LOUZADA, FRANCISCO. Optimal burn-in policy based on a set of cutoff points using mixture inverse Gaussian degradation process and copulas. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, . (17/25971-0, 13/07375-0)
DE SOUZA, HAYALA CRISTINA CAVENAGUE; LOUZADA, FRANCISCO; RAMOS, PEDRO LUIZ; DE OLIVEIRA JUNIOR, MAURO RIBEIRO; PERDONA, GLEICI DA SILVA CASTRO. A Bayesian approach for the zero-inflated cure model: an application in a Brazilian invasive cervical cancer database. Journal of Applied Statistics, . (17/25971-0)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.