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Author Leao, J.; Leiva, V.; Saulo, H.; Tomazella, V.
Title Birnbaum-Saunders frailty regression models: Diagnostics and application to medical data Type
Year 2017 Publication Biometrical Journal Abbreviated Journal Biom. J.
Volume 59 Issue 2 Pages 291-314
Keywords Birnbaum-Saunders distribution; Censored data; Global and local influence; Maximum-likelihood method; Residual analysis
Abstract In survival models, some covariates affecting the lifetime could not be observed or measured. These covariates may correspond to environmental or genetic factors and be considered as a random effect related to a frailty of the individuals explaining their survival times. We propose a methodology based on a Birnbaum-Saunders frailty regression model, which can be applied to censored or uncensored data. Maximum-likelihood methods are used to estimate the model parameters and to derive local influence techniques. Diagnostic tools are important in regression to detect anomalies, as departures from error assumptions and presence of outliers and influential cases. Normal curvatures for local influence under different perturbations are computed and two types of residuals are introduced. Two examples with uncensored and censored real-world data illustrate the proposed methodology. Comparison with classical frailty models is carried out in these examples, which shows the superiority of the proposed model.
Address [Leao, Jeremias] Univ Fed Amazonas, Dept Stat, Manaus, Amazonas, Brazil, Email: victorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Wiley Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0323-3847 ISBN Medium
Area Expedition Conference
Notes WOS:000396452500006 Approved
Call Number UAI @ eduardo.moreno @ Serial 707
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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 Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0167-9473 ISBN Medium
Area Expedition Conference
Notes WOS:000340139900013 Approved
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
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0340-1200 ISBN Medium
Area Expedition Conference
Notes WOS:000361484300001 Approved
Call Number UAI @ eduardo.moreno @ Serial 528
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Author Marchant, C.; Leiva, V.; Cysneiros, F.J.A.
Title A Multivariate Log-Linear Model for Birnbaum-Saunders Distributions Type
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 Thesis
Publisher Ieee-Inst Electrical Electronics Engineers Inc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0018-9529 ISBN Medium
Area Expedition Conference
Notes WOS:000382706900027 Approved
Call Number UAI @ eduardo.moreno @ Serial 653
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Author Marchant, C.; Leiva, V.; Cysneiros, F.J.A.; Vivanco, J.F.
Title Diagnostics in multivariate generalized Birnbaum-Saunders regression models Type
Year 2016 Publication Journal Of Applied Statistics Abbreviated Journal J. Appl. Stat.
Volume 43 Issue 15 Pages 2829-2849
Keywords Birnbaum-Saunders distributions; global and local influence; goodness-of-fit; multivariate data analysis; R software
Abstract Birnbaum-Saunders (BS) models are receiving considerable attention in the literature. Multivariate regression models are a useful tool of the multivariate analysis, which takes into account the correlation between variables. Diagnostic analysis is an important aspect to be considered in the statistical modeling. In this paper, we formulate multivariate generalized BS regression models and carry out a diagnostic analysis for these models. We consider the Mahalanobis distance as a global influence measure to detect multivariate outliers and use it for evaluating the adequacy of the distributional assumption. We also consider the local influence approach and study how a perturbation may impact on the estimation of model parameters. We implement the obtained results in the R software, which are illustrated with real-world multivariate data to show their potential applications.
Address [Marchant, Carolina; Cysneiros, Francisco Jose A.] Univ Fed Pernambuco, Dept Stat, Recife, PE, Brazil, Email: victorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Taylor & Francis Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0266-4763 ISBN Medium
Area Expedition Conference
Notes WOS:000384263000009 Approved
Call Number UAI @ eduardo.moreno @ Serial 662
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Author Martinez, C.; Aguilar, C.; Briones, E.; Guzman, D.; Zelaya, E.; Troncoso, L.; Roja, P.A.
Title Effects of Zr on the amorphization of Cu-Ni-Zr alloys prepared by mechanical alloying Type
Year 2018 Publication Journal of Alloys and Compounds Abbreviated Journal J. Alloys Compd.
Volume 765 Issue Pages 771-781
Keywords BULK METALLIC GLASSES; SOLID-SOLUTION; CRYSTALLINE; FABRICATION; EVOLUTION; POWDERS; SYSTEM; NB; TI
Abstract This work presents the effects of high energy milling with different Ni and Zr ratios on the amorphization of ternary Cu-Ni-Zr alloys (initially, Cu-43Ni-7Zr, Cu-12Ni-31Zr, Cu-33Ni-7Zr, and Cu-12Ni-23Zr; and later, Cu-23Ni-15Zr and Cu-11Ni-7Zr). Microstructure was determined using X-Ray diffraction and electron microscopy. Results were compared to thermodynamic models. In the ternary alloys under study, the lattice parameter of the Cu-Ni solid solution was generally correlated to the amounts of nickel incorporated into the Cu lattice. However, longer milling times reduced that lattice parameter and facilitated Zr insertion into the solid solution. For example, after 5 h of milling time, microstructural analysis showed the formation of a solid solution with cubic structure in Cu-43Ni-7Zr. This pattern is consistent with the presence of a lattice parameter between that of Cu and Ni (alpha-phase); in contrast, the Cu-33Ni-7Zr alloy showed an alpha-phase and another similar to Zr. Results suggest that, as the amount of nickel increases, the ability to form an amorphous phase decreases. Additionally, experimental and thermodynamic data showed a solid-solution formation stage, followed by an amorphous phase formation stage that occurred as milling time and Zr content increased. (C) 2018 Published by Elsevier B.V.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0925-8388 ISBN Medium
Area Expedition Conference
Notes WOS:000444341900095 Approved
Call Number UAI @ alexi.delcanto @ Serial 1406
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Author Miranda, A.; Mentler, R.; Moletto-Lobos, I.; Alfaro, G.; Aliaga, L.; Balbontin, D.; Barraza, M.; Baumbach, S.; Calderon, P.; Cardenas, F.; Castillo, I.; Contreras, G.; de la Barra, F.; Galleguillos, M.; Gonzalez, M.E.; Hormazabal, C.; Lara, A.; Mancilla, I.; Munoz, F.; Oyarce, C.; Pantoja, F.; Ramirez, R.; Urrutia, V.
Title The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile Type
Year 2022 Publication Earth System Science Data Abbreviated Journal Earth Syst. Sci. Data
Volume 14 Issue 8 Pages 3599-3613
Keywords TIME-SERIES; LAND-USE; ALGORITHM; WILDFIRES; IMPACTS; RDNBR
Abstract Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic databases. High-quality information can help to transform evidence into decision-making in the context of rapidly changing landscapes, particularly considering that geographical and temporal patterns of fire regimes and their trends vary locally over time. Global fire scar products at low spatial resolutions are available, but high-resolution wildfire data, especially for developing countries, are still lacking. Taking advantage of the Google Earth Engine (GEE) big-data analysis platform, we developed a flexible workflow to reconstruct individual burned areas and derive fire severity estimates for all reported fires. We tested our approach for historical wild-fires in Chile. The result is the Landscape Fire Scars Database, a detailed and dynamic database that reconstructs 8153 fires scars, representing 66.6% of the country's officially recorded fires between 1985 and 2018. For each fire event, the database contains the following information: (i) the Landsat mosaic of pre- and post-fire images; (ii) the fire scar in binary format; (iii) the remotely sensed estimated fire indexes (the normalized burned ratio, NBR, and the relative delta normalized burn ratio, RdNBR); and two vector files indicating (iv) the fire scar perimeter and (v) the fire scar severity reclassification, respectively. The Landscape Fire Scars Database for Chile and GEE script (JavaScript) are publicly available. The framework developed for the database can be applied anywhere in the world, with the only requirement being its adaptation to local factors such as data availability, fire regimes, land cover or land cover dynamics, vegetation recovery, and cloud cover. The Landscape Fire Scars Database for Chile is publicly available in https://doi.org/10.1594/PANGAEA.941127 (Miranda et al., 2022).
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1866-3508 ISBN Medium
Area Expedition Conference
Notes WOS:000838024900001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1667
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Author Sanchez, R.; Briones, M.J.; Gamboa, A.; Monsalve, R.; Berroeta, D.; Valenzuela, L.
Title Delimitation of burned areas in Chile based on dNBR thresholds adjusted according to region and land cover Type
Year 2023 Publication Revista de Teledeteccion Abbreviated Journal Rev. de Teledeteccion
Volume 61 Issue Pages 43-58
Keywords dNBR; Landsat-8; mega fire; multispectral images; burn severity; area delimitation
Abstract The delimitation of burned areas is an important step for the study of forest fires, and the use of satellite remote sensing allows a scalable methodology. Previous studies use a dNBR threshold to determine the presence of burned areas, but this threshold is affected by vegetation variability determined by the geography of the study area and land use coverage. For them, the difference in the normalized index of burned areas (dNBR) was used to study the mega fires that affected the central zone of Chile in the summer of 2017. An automated methodology was developed that, based on satellite images and polygons of the burned areas provided by the National Forestry Corporation of Chile (CONAF) generates a set of dNBR thresholds differentiated by administrative region and land use. The application of differentiated dNBR thresholds significantly improves the accuracy of the burnt area delimitation model, although it does not achieve satisfactory results for all land uses. This methodological advance will make it possible to improve the design and control of policies for the prevention, conservation and restoration of ecosystems affected by forest fires.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1133-0953 ISBN Medium
Area Expedition Conference
Notes WOS:000963597500004 Approved
Call Number UAI @ alexi.delcanto @ Serial 1776
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Author Santos-Neto, M.; Cysneiros, F.J.A.; Leiva, V.; Barros, M.
Title Reparameterized Birnbaum-Saunders regression models with varying precision Type
Year 2016 Publication Electronic Journal Of Statistics Abbreviated Journal Electron. J. Stat.
Volume 10 Issue 2 Pages 2825-2855
Keywords Birnbaum-Saunders distribution; hypothesis testing; likelihood-based methods; local influence; Monte Carlo simulation; residuals; R software
Abstract We propose a methodology based on a reparameterized Birnbaum-Saunders regression model with varying precision, which generalizes the existing works in the literature on the topic. This methodology includes the estimation of model parameters, hypothesis tests for the precision parameter, a residual analysis and influence diagnostic tools. Simulation studies are conducted to evaluate its performance. We apply it to two real-world case-studies to show its potential with the R software.
Address [Santos-Neto, Manoel; Barros, Michelli] Univ Fed Campina Grande, Dept Stat, Campina Grande, Brazil, Email: manoel.ferreira@ufcg.edu.br;
Corporate Author Thesis
Publisher Inst Mathematical Statistics Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1935-7524 ISBN Medium
Area Expedition Conference
Notes WOS:000390364400036 Approved
Call Number UAI @ eduardo.moreno @ Serial 684
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