| Records |
| Author |
Fierro, R.; Leiva, V.; Balakrishnan, N. |
| Title |
Statistical Inference on a Stochastic Epidemic Model |
Type |
|
| Year |
2015 |
Publication |
Communications In Statistics-Simulation And Computation |
Abbreviated Journal |
Commun. Stat.-Simul. Comput. |
| Volume |
44 |
Issue |
9 |
Pages |
2297-2314 |
| Keywords |
Asymptotic normality; Chi-squared test; Markov chains; Martingale estimators; Maximum likelihood estimators; SIR epidemic model |
| Abstract |
In this work, we develop statistical inference for the parameters of a discrete-time stochastic SIR epidemic model. We use a Markov chain for describing the dynamic behavior of the epidemic. Specifically, we propose estimators for the contact and removal rates based on the maximum likelihood and martingale methods, and establish their asymptotic distributions. The obtained results are applied in the statistical analysis of the basic reproduction number, a quantity that is useful in establishing vaccination policies. In order to evaluate the population size for which the results are useful, a numerical study is carried out. Finally, a comparison of the maximum likelihood and martingale estimators is conducted by means of Monte Carlo simulations. |
| Address |
[Fierro, Raul] Pontificia Univ Catolica Valparaiso, Inst Matemat, Valparaiso, Chile, Email: victorleivasanchez@gmail.com |
| Corporate Author |
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Thesis |
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| Publisher |
Taylor & Francis Inc |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0361-0918 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000356808000008 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
506 |
| Permanent link to this record |
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| Author |
Leiva, V.; Saulo, H.; Leao, J.; Marchant, C. |
| Title |
A family of autoregressive conditional duration models applied to financial data |
Type |
|
| Year |
2014 |
Publication |
Computational Statistics & Data Analysis |
Abbreviated Journal |
Comput. Stat. Data Anal. |
| Volume |
79 |
Issue |
|
Pages |
175-191 |
| Keywords |
Birnbaum-Saunders distribution; EM algorithm; High-frequency data; Maximum likelihood estimator; Monte Carlo simulation |
| Abstract |
The Birnbaum-Saunders distribution is receiving considerable attention due to its good properties. One of its extensions is the class of scale-mixture Birnbaum-Saunders (SBS) distributions, which shares its good properties, but it also has further properties. The autoregressive conditional duration models are the primary family used for analyzing high-frequency financial data. We propose a methodology based on SBS autoregressive conditional duration models, which includes in-sample inference, goodness-of-fit and out-of-sample forecast techniques. We carry out a Monte Carlo study to evaluate its performance and assess its practical usefulness with real-world data of financial transactions from the New York stock exchange. (C) 2014 Elsevier B.V. All rights reserved. |
| Address |
[Leiva, Victor; Marchant, Carolina] Univ Valparaiso, Inst Estadist, Valparaiso, Chile, Email: victor.leiva@yahoo.com |
| Corporate Author |
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Thesis |
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| Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0167-9473 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000340139900013 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
396 |
| Permanent link to this record |
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| Author |
Liu, S.Z.; Leiva, V.; Ma, T.F.; Welsh, A. |
| Title |
Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions |
Type |
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| Year |
2016 |
Publication |
Statistical Methods And Applications |
Abbreviated Journal |
Stat. Method. Appl. |
| Volume |
25 |
Issue |
2 |
Pages |
227-249 |
| Keywords |
Information matrix; Local influence; Restricted least-squares estimator; Restricted maximum likelihood estimator |
| Abstract |
The local influence method has proven to be a useful and powerful tool for detecting influential observations on the estimation of model parameters. This method has been widely applied in different studies related to econometric and statistical modelling. We propose a methodology based on the Lagrange multiplier method with a linear penalty function to assess local influence in the possibly heteroskedastic linear regression model with exact restrictions. The restricted maximum likelihood estimators and information matrices are presented for the postulated model. Several perturbation schemes for the local influence method are investigated to identify potentially influential observations. Three real-world examples are included to illustrate and validate our methodology. |
| Address |
[Liu, Shuangzhe] Univ Canberra, Fac Educ Sci Technol & Math, Canberra, ACT 2601, Australia, Email: shuangzhe.liu@canberra.edu.au; |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Heidelberg |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1618-2510 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000376996500004 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
632 |
| Permanent link to this record |
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| Author |
Sanchez, L.; Leiva, V.; Caro-Lopera, F.J.; Cysneiros, F.J.A. |
| Title |
On matrix-variate Birnbaum-Saunders distributions and their estimation and application |
Type |
|
| Year |
2015 |
Publication |
Brazilian Journal Of Probability And Statistics |
Abbreviated Journal |
Braz. J. Probab. Stat. |
| Volume |
29 |
Issue |
4 |
Pages |
790-812 |
| Keywords |
Computer language; data analysis; elliptically contoured distribution; maximum likelihood estimator; Monte Carlo method; shape theory |
| Abstract |
Diverse phenomena from the real-world can be modeled using random matrices, allowing matrix-variate distributions to be considered. The normal distribution is often employed in this modeling, but usually the mentioned random matrices do not follow such a distribution. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum-Saunders (BS) distribution. We propose a statistical methodology based on matrix-variate BS distributions. This methodology is implemented in the statistical software R. A simulation study is conducted to evaluate its performance. Finally, an application with real-world matrix-variate data is carried out to illustrate its potentiality and suitability. |
| Address |
[Sanchez, Luis] Univ Valparaiso, Inst Estadist, Valparaiso, Chile, Email: ldaniel9.24@gmail.com; |
| Corporate Author |
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Thesis |
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| Publisher |
Brazilian Statistical Association |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0103-0752 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000362310900005 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
621 |
| Permanent link to this record |
