Yespenalized is a exible, extensible, and e cient MATLAB toolbox for penalized maximum likelihood. penalized allows you to t a generalized linear model (gaussian, logistic, poisson, or multinomial) using any of ten provided penalties, or none. The toolbox can be extended by creating new maximum likelihood models or new penalties. The toolbox also includes routines for cross-validation and plotting
The use of regularization, or penalization, has become increasingly common in highdimensional statis...
Penalized factor analysis is an efficient technique that produces a factor loading matrix with many ...
Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable ...
Penalized estimation has become an established tool for regularization and model selection in regres...
Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, thei...
In high dimensional regression problems penalization techniques are a useful tool for estimation and...
Summary. Penalized likelihood methods provide a range of practical modelling tools, including spline...
© 2014 Dr. David LazaridisMaximum likelihood (ML) or restricted maximum likelihood (REML) are typica...
peer reviewedFor numerous applications, it is of interest to provide full probabilistic forecasts, ...
grantor: University of TorontoBridge regression, a special type of penalized regression of...
University of Minnesota Ph.D. dissertation.September 2015. Major: Statistics. Advisor: Hui Zou. 1 co...
The use of regularization, or penalization, has become increasingly common in highdimensional statis...
Penalized factor analysis is an efficient technique that produces a factor loading matrix with many ...
Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable ...
Penalized estimation has become an established tool for regularization and model selection in regres...
Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, thei...
In high dimensional regression problems penalization techniques are a useful tool for estimation and...
Summary. Penalized likelihood methods provide a range of practical modelling tools, including spline...
© 2014 Dr. David LazaridisMaximum likelihood (ML) or restricted maximum likelihood (REML) are typica...
peer reviewedFor numerous applications, it is of interest to provide full probabilistic forecasts, ...
grantor: University of TorontoBridge regression, a special type of penalized regression of...
University of Minnesota Ph.D. dissertation.September 2015. Major: Statistics. Advisor: Hui Zou. 1 co...
The use of regularization, or penalization, has become increasingly common in highdimensional statis...
Penalized factor analysis is an efficient technique that produces a factor loading matrix with many ...
Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable ...