| Records |
| Author |
Barros, M.; Galea, M.; Leiva, V.; Santos-Neto, M. |
| Title |
Generalized Tobit models: diagnostics and application in econometrics |
Type |
|
| Year |
2018 |
Publication |
Journal Of Applied Statistics |
Abbreviated Journal |
J. Appl. Stat. |
| Volume |
45 |
Issue |
1 |
Pages |
145-167 |
| Keywords |
Cook distance; elliptically contoured distributions; labor supply data; local influence method; maximum likelihood method; R software; residuals; Student-t distribution |
| Abstract |
The standard Tobit model is constructed under the assumption of a normal distribution and has been widely applied in econometrics. Atypical/extreme data have a harmful effect on the maximum likelihood estimates of the standard Tobit model parameters. Then, we need to count with diagnostic tools to evaluate the effect of extreme data. If they are detected, we must have available a Tobit model that is robust to this type of data. The family of elliptically contoured distributions has the Laplace, logistic, normal and Student-t cases as some of its members. This family has been largely used for providing generalizations of models based on the normal distribution, with excellent practical results. In particular, because the Student-t distribution has an additional parameter, we can adjust the kurtosis of the data, providing robust estimates against extreme data. We propose a methodology based on a generalization of the standard Tobit model with errors following elliptical distributions. Diagnostics in the Tobit model with elliptical errors are developed. We derive residuals and global/local influence methods considering several perturbation schemes. This is important because different diagnostic methods can detect different atypical data. We implement the proposed methodology in an R package. We illustrate the methodology with real-world econometrical data by using the R package, which shows its potential applications. The Tobit model based on the Student-t distribution with a small quantity of degrees of freedom displays an excellent performance reducing the influence of extreme cases in the maximum likelihood estimates in the application presented. It provides new empirical evidence on the capabilities of the Student-t distribution for accommodation of atypical data. |
| Address |
[Barros, Michelli; Santos-Neto, Manoel] Univ Fed Campina Grande, Dept Stat, Campina Grande, Brazil, Email: victorleivasanchez@gmail.com |
| Corporate Author |
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Thesis |
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| Publisher |
Taylor & Francis Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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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 |
0266-4763 |
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:000415929600011 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
781 |
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| Author |
Celis, P.; de la Cruz, R.; Fuentes, C.; Gomez, HW. |
| Title |
Survival and Reliability Analysis with an Epsilon-Positive Family of Distributions with Applications |
Type |
|
| Year |
2021 |
Publication |
Symmetry-Basel |
Abbreviated Journal |
Symmetry |
| Volume |
13 |
Issue |
5 |
Pages |
908 |
| Keywords |
censored data; EM algorithm; epsilon– exponential distribution; exponential distribution; maximum likelihood; reliability analysis; survival analysis; stress-strength parameter |
| Abstract |
We introduce a new class of distributions called the epsilon-positive family, which can be viewed as generalization of the distributions with positive support. The construction of the epsilon-positive family is motivated by the ideas behind the generation of skew distributions using symmetric kernels. This new class of distributions has as special cases the exponential, Weibull, log-normal, log-logistic and gamma distributions, and it provides an alternative for analyzing reliability and survival data. An interesting feature of the epsilon-positive family is that it can viewed as a finite scale mixture of positive distributions, facilitating the derivation and implementation of EM-type algorithms to obtain maximum likelihood estimates (MLE) with (un)censored data. We illustrate the flexibility of this family to analyze censored and uncensored data using two real examples. One of them was previously discussed in the literature; the second one consists of a new application to model recidivism data of a group of inmates released from the Chilean prisons during 2007. The results show that this new family of distributions has a better performance fitting the data than some common alternatives such as the exponential distribution. |
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Series Issue |
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Edition |
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| ISSN |
2073-8994 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000654702000001 |
Approved |
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| Call Number |
UAI @ alexi.delcanto @ |
Serial |
1384 |
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| Author |
Faouzi, T.; Porcu, E.; Bevilacqua, M. |
| Title |
SPACE-TIME ESTIMATION AND PREDICTION UNDER FIXED-DOMAIN ASYMPTOTICS WITH COMPACTLY SUPPORTED COVARIANCE FUNCTIONS |
Type |
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| Year |
2022 |
Publication |
Statistica Sinica |
Abbreviated Journal |
Stat. Sin. |
| Volume |
32 |
Issue |
3 |
Pages |
1187-1203 |
| Keywords |
Fixed-domain asymptotics; microergodic parameter; maximum likelihood; space-time generalized wendland family |
| Abstract |
We study the estimation and prediction of Gaussian processes with spacetime covariance models belonging to the dynamical generalized Wendland (DGW) family, under fixed-domain asymptotics. Such a class is nonseparable, has dynamical compact supports, and parameterizes differentiability at the origin similarly to the space-time Matern class.
Our results are presented in two parts. First, we establish the strong consistency and asymptotic normality for the maximum likelihood estimator of the microergodic parameter associated with the DGW covariance model, under fixed-domain asymptotics. The second part focuses on optimal kriging prediction under the DGW model and an asymptotically correct estimation of the mean squared error using a misspecified model. Our theoretical results are, in turn, based on the equivalence of Gaussian measures under some given families of space-time covariance functions, where both space or time are compact. The technical results are provided in the online Supplementary material. |
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Place of Publication |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1017-0405 |
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:000818975200001 |
Approved |
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| Call Number |
UAI @ alexi.delcanto @ |
Serial |
1599 |
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| Author |
Fierro, R.; Leiva, V.; Balakrishnan, N. |
| Title |
Statistical Inference on a Stochastic Epidemic Model |
Type |
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| 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 |
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| Author |
Garcia-Papani, F.; Uribe-Opazo, M.A.; Leiva, V.; Aykroyd, R.G. |
| Title |
Birnbaum-Saunders spatial modelling and diagnostics applied to agricultural engineering data |
Type |
|
| Year |
2017 |
Publication |
Stochastic Environmental Research And Risk Assessment |
Abbreviated Journal |
Stoch. Environ. Res. Risk Assess. |
| Volume |
31 |
Issue |
1 |
Pages |
105-124 |
| Keywords |
Asymmetric distributions; Local influence; Matern model; Maximum likelihood methods; Monte Carlo simulation; Non-normality; R software; Spatial data analysis |
| Abstract |
Applications of statistical models to describe spatial dependence in geo-referenced data are widespread across many disciplines including the environmental sciences. Most of these applications assume that the data follow a Gaussian distribution. However, in many of them the normality assumption, and even a more general assumption of symmetry, are not appropriate. In non-spatial applications, where the data are uni-modal and positively skewed, the Birnbaum-Saunders (BS) distribution has excelled. This paper proposes a spatial log-linear model based on the BS distribution. Model parameters are estimated using the maximum likelihood method. Local influence diagnostics are derived to assess the sensitivity of the estimators to perturbations in the response variable. As illustration, the proposed model and its diagnostics are used to analyse a real-world agricultural data set, where the spatial variability of phosphorus concentration in the soil is considered-which is extremely important for agricultural management. |
| Address |
[Garcia-Papani, Fabiana; Uribe-Opazo, Miguel Angel] Univ Estadual Oeste Parana, Postgrad Program Agr Engn, Ctr Exact Sci & Technol, Cascavel, PR, Brazil, Email: fgarciapapani@gmail.com; |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
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 |
1436-3240 |
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:000394278600008 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
704 |
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| Author |
Leiva, V.; Ferreira, M.; Gomes, M.I.; Lillo, C. |
| Title |
Extreme value Birnbaum-Saunders regression models applied to environmental data |
Type |
|
| Year |
2016 |
Publication |
Stochastic Environmental Research And Risk Assessment |
Abbreviated Journal |
Stoch. Environ. Res. Risk Assess. |
| Volume |
30 |
Issue |
3 |
Pages |
1045-1058 |
| Keywords |
Data analysis; Maximum likelihood method; Monte Carlo simulation; Residuals; Statistical modeling |
| Abstract |
Extreme value models are widely used in different areas. The Birnbaum-Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum-Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration. |
| Address |
[Leiva, Victor] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago, Chile, Email: victorleivasanchez@gmail.com |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
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 |
1436-3240 |
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:000371316900019 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
585 |
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| Author |
Leiva, V.; Santos-Neto, M.; Cysneiros, F.J.A.; Barros, M. |
| Title |
A methodology for stochastic inventory models based on a zero-adjusted Birnbaum-Saunders distribution |
Type |
|
| Year |
2016 |
Publication |
Applied Stochastic Models In Business And Industry |
Abbreviated Journal |
Appl. Stoch. Models. Bus. Ind. |
| Volume |
32 |
Issue |
1 |
Pages |
74-89 |
| Keywords |
demand data; financial indicators; maximum likelihood method; mixture distributions; Monte Carlo simulation; R software |
| Abstract |
The Birnbaum-Saunders (BS) distribution is receiving considerable attention. We propose a methodology for inventory logistics that allows demand data with zeros to be modeled by means of a new discrete-continuous mixture distribution, which is constructed by using a probability mass at zero and a continuous component related to the BS distribution. We obtain some properties of the new mixture distribution and conduct a simulation study to evaluate the performance of the estimators of its parameters. The methodology for stochastic inventory models considers also financial indicators. We illustrate the proposed methodology with two real-world demand data sets. It shows its potential, highlighting the convenience of using it by improving the contribution margins of a Chilean food industry. Copyright (c) 2015 John Wiley & Sons, Ltd. |
| Address |
[Leiva, Victor] Univ Valparaiso, Inst Stat, Valparaiso, Chile, Email: victorleivasanchez@gmail.com |
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Thesis |
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| Publisher |
Wiley-Blackwell |
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 |
1524-1904 |
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:000369134600006 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
580 |
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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 |
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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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Abbreviated Series Title |
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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 |
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| Author |
Leiva, V.; Tejo, M.; Guiraud, P.; Schmachtenberg, O.; Orio, P.; Marmolejo-Ramos, F. |
| Title |
Modeling neural activity with cumulative damage distributions |
Type |
|
| Year |
2015 |
Publication |
Biological Cybernetics |
Abbreviated Journal |
Biol. Cybern. |
| Volume |
109 |
Issue |
4-5 |
Pages |
421-433 |
| Keywords |
Birnbaum-Saunders and inverse Gaussian distributions; Integrate-and-fire model; Inter-spike intervals; Maximum likelihood method; Model selection and goodness of fit |
| Abstract |
Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum-Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum-Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data. |
| Address |
[Leiva, Victor] Univ Adolfo Ibanez, Fac Sci & Engn, Vina Del Mar, Chile, Email: victorleivasanchez@gmail.com |
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Thesis |
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| Publisher |
Springer |
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 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 |
0340-1200 |
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:000361484300001 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
528 |
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| Author |
Lillo, C.; Leiva, V.; Nicolis, O.; Aykroyd, R.G. |
| Title |
L-moments of the Birnbaum-Saunders distribution and its extreme value version: estimation, goodness of fit and application to earthquake data |
Type |
|
| Year |
2018 |
Publication |
Journal Of Applied Statistics |
Abbreviated Journal |
J. Appl. Stat. |
| Volume |
45 |
Issue |
2 |
Pages |
187-209 |
| Keywords |
GCMT catalogue; Generalized extreme value distributions; goodness-of-fit methods; maximum likelihood and moment estimation; Monte Carlo simulation; R software |
| Abstract |
Understanding patterns in the frequency of extreme natural events, such as earthquakes, is important as it helps in the prediction of their future occurrence and hence provides better civil protection. Distributions describing these events are known to be heavy tailed and positive skew making standard distributions unsuitable for modelling the frequency of such events. The Birnbaum-Saunders distribution and its extreme value version have been widely studied and applied due to their attractive properties. We derive L-moment equations for these distributions and propose novel methods for parameter estimation, goodness-of-fit assessment and model selection. A simulation study is conducted to evaluate the performance of the L-moment estimators, which is compared to that of the maximum likelihood estimators, demonstrating the superiority of the proposed methods. To illustrate these methods in a practical application, a data analysis of real-world earthquake magnitudes, obtained from the global centroid moment tensor catalogue during 1962-2015, is carried out. This application identifies the extreme value Birnbaum-Saunders distribution as a better model than classic extreme value distributions for describing seismic events. |
| Address |
[Lillo, Camilo; Leiva, Victor] Univ Adolfo Ibanez, Fac Sci & Engn, Vina Del Mar, Chile, Email: victorleivasanchez@gmail.com |
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Thesis |
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| Publisher |
Taylor & Francis Ltd |
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 |
0266-4763 |
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:000417787500001 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
780 |
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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 |
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| Author |
Marchant, C.; Leiva, V.; Cysneiros, F.J.A. |
| Title |
A Multivariate Log-Linear Model for Birnbaum-Saunders Distributions |
Type |
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| Year |
2016 |
Publication |
Ieee Transactions On Reliability |
Abbreviated Journal |
IEEE Trans. Reliab. |
| Volume |
65 |
Issue |
2 |
Pages |
816-827 |
| Keywords |
EM algorithm; fatigue data; logarithmic distributions; maximum likelihood method; Monte Carlo simulation; multivariate generalized Birnbaum-Saunders distributions; R software |
| Abstract |
Univariate Birnbaum-Saunders models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new models with real-world multivariate fatigue data. |
| Address |
[Marchant, Carolina] Univ Fed Pernambuco, Recife, PE, Brazil, Email: carolina.marchant.fuentes@gmail.com; |
| Corporate Author |
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Thesis |
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| Publisher |
Ieee-Inst Electrical Electronics Engineers 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 Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0018-9529 |
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:000382706900027 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
653 |
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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 |
|
| Call Number |
UAI @ eduardo.moreno @ |
Serial |
621 |
| Permanent link to this record |
| |
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| |
| Author |
Santos-Neto, M.; Cysneiros, F.J.A.; Leiva, V.; Barros, M. |
| Title |
A Reparameterized Birnbaum-Saunders Distribution And Its Moments, Estimation And Applications |
Type |
|
| Year |
2014 |
Publication |
REVSTAT-Statistical Journal |
Abbreviated Journal |
REVSTAT-Stat. J. |
| Volume |
12 |
Issue |
3 |
Pages |
247-272 |
| Keywords |
data analysis; maximum likelihood and moment estimation; Monte Carlo method; random number generation; statistical software |
| Abstract |
The Birnbaum-Saunders (BS) distribution is a model that is receiving considerable attention due to its good properties. We provide some results on moments of a reparameterized version of the BS distribution and a generation method of random numbers from this distribution. In addition, we propose estimation and inference for the mentioned parameterization based on maximum likelihood, moment, modified moment and generalized moment methods. By means of a Monte Carlo simulation study, we evaluate the performance of the proposed estimators. We discuss applications of the reparameterized BS distribution from different scientific fields and analyze two real-world data sets to illustrate our results. The simulated and real data are analyzed by using the R software. |
| Address |
[Santos-Neto, Manoel; Barros, Michelli] Univ Fed Campina Grande, Dept Estat, Campina Grande, Brazil, Email: manoel.ferreira@ufcg.edu.br; |
| Corporate Author |
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Thesis |
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| Publisher |
Inst Nacional Estatistica-Ine |
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 |
|
Edition |
|
| ISSN |
1645-6726 |
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:000349017700003 |
Approved |
|
| Call Number |
UAI @ eduardo.moreno @ |
Serial |
448 |
| Permanent link to this record |
