Machine learning in materials genome initiative: A review
Y Liu, C Niu, Z Wang, Y Gan, Y Zhu, S Sun… - Journal of Materials …, 2020 - Elsevier
Discovering new materials with excellent performance is a hot issue in the materials
genome initiative. Traditional experiments and calculations often waste large amounts of …
genome initiative. Traditional experiments and calculations often waste large amounts of …
Birnbaum‐Saunders distribution: A review of models, analysis, and applications
N Balakrishnan, D Kundu - Applied Stochastic Models in …, 2019 - Wiley Online Library
Birnbaum and Saunders introduced a two‐parameter lifetime distribution to model the
fatigue life of a metal, subject to cyclic stress. Since then, extensive work has been done on …
fatigue life of a metal, subject to cyclic stress. Since then, extensive work has been done on …
Birnbaum‐Saunders quantile regression and its diagnostics with application to economic data
Abstract The Birnbaum‐Saunders (BS) distribution is a model that frequently appears in the
statistical literature and has proved to be very versatile and efficient across a wide range of …
statistical literature and has proved to be very versatile and efficient across a wide range of …
An overview on parametric quantile regression models and their computational implementation with applications to biomedical problems including COVID-19 data
Quantile regression allows us to estimate the relationship between covariates and any
quantile of the response variable rather than the mean. Recently, several statistical …
quantile of the response variable rather than the mean. Recently, several statistical …
Log‐symmetric quantile regression models
Regression models based on the log‐symmetric family of distributions are particularly useful
when the response variable is continuous, positive, and asymmetrically distributed. In this …
when the response variable is continuous, positive, and asymmetrically distributed. In this …
On a partial least squares regression model for asymmetric data with a chemical application in mining
In chemometrical applications, covariates in regression models are often correlated, causing
a collinearity problem that can be solved by partial least squares (PLS) regression. In …
a collinearity problem that can be solved by partial least squares (PLS) regression. In …
Birnbaum-Saunders quantile regression models with application to spatial data
In the present paper, a novel spatial quantile regression model based on the Birnbaum–
Saunders distribution is formulated. This distribution has been widely studied and applied in …
Saunders distribution is formulated. This distribution has been widely studied and applied in …
Incorporation of frailties into a cure rate regression model and its diagnostics and application to melanoma data
Cure rate models have been widely studied to analyze time‐to‐event data with a cured
fraction of patients. Our proposal consists of incorporating frailty into a cure rate model, as an …
fraction of patients. Our proposal consists of incorporating frailty into a cure rate model, as an …
Cokriging prediction using as secondary variable a functional random field with application in environmental pollution
Cokriging is a geostatistical technique that is used for spatial prediction when realizations of
a random field are available. If a secondary variable is cross-correlated with the primary …
a random field are available. If a secondary variable is cross-correlated with the primary …
A new BISARMA time series model for forecasting mortality using weather and particulate matter data
Abstract The Birnbaum–Saunders (BS) distribution is a model that frequently appears in the
statistical literature and has proved to be very versatile and efficient across a wide range of …
statistical literature and has proved to be very versatile and efficient across a wide range of …