Mulr4FL: Effective Fault Localization of Evolution Software Based on Multivariate Logistic Regression Model

Tutorial on Multivariate Logistic Regression

Bayesian multivariate logistic regression.

Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual outcomes. In addition, difficulties arise when simple noninformative priors are chosen for the covariance parameters. Motivated by these problems, we propose a new type of multivariate logistic dis...

Effective fault localization techniques for concurrent software

ACKNOWLEDGEMENTS First of all, I must express my utmost gratitude to my advisor, Dr. Mary Jean Harrold, for her unlimited support. Mary Jean helped me in all aspects of research from finding a research topic to writing a good research paper. Also, she gave me advice to be a good researcher as well as a good person. I am deeply indebted to Dr. Richard Vuduc. Rich has been a good research mentor ...

Outcomes of High-Risk Pregnancies in Northern Iran: Multivariate Logistic Regression Model

Abstract Background and purpose: High-risk pregnancy is referred to a situation in which mother, fetus or neonate are in higher risk of morbidity or mortality. Because of adverse outcomes of high-risk pregnancies, this study aims to determine these outcomes in the North of Iran.  Materials and Methods: We recruited 803 urban and rural pregnant women in this crosssectional ...

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...