Results 21 to 30 of about 4,586 (136)
Ridge Estimation for Multinomial Logit Models with Symmetric Side Constraints [PDF]
, 2009 In multinomial logit models, the identifiability of parameter estimates is typically obtained by side constraints that specify one of the response categories as reference category.
Tutz, Gerhard, Zahid, Faisal Maqbool
core +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Variable Selection in General Multinomial Logit Models [PDF]
, 2012 The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood estimates tend to deteriorate.
Pößnecker, Wolfgang +2 more
core +2 more sources
Beyond the Ban—Shedding Light on Smallholders' Price Vulnerability in Indonesia's Palm Oil Industry
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT The Indonesian government imposed a palm oil export ban in April 2022 to address rising cooking oil prices. This study explores oil palm smallholders' vulnerability to the policy using descriptive statistics, Lasso, and post‐Lasso OLS regressions.
Charlotte‐Elena Reich +3 more
wiley +1 more source
Preliminary test and Stein-type shrinkage LASSO-based estimators [PDF]
, 2018 Peer ...
Arashi, Mohammad, Norouzirad, Mina
core
The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery, EarlyView.As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson +6 more
wiley +1 more source
Adaptive Monotone Shrinkage for Regression [PDF]
, 2015 We develop an adaptive monotone shrinkage estimator for regression models with the following characteristics: i) dense coefficients with small but important effects; ii) a priori ordering that indicates the probable predictive importance of the features.
Foster, Dean, Ma, Zhuang, Stine, Robert
core
Beyond Support in Two-Stage Variable Selection [PDF]
, 2015 Numerous variable selection methods rely on a two-stage procedure, where a sparsity-inducing penalty is used in the first stage to predict the support, which is then conveyed to the second stage for estimation or inference purposes.
Ambroise, Christophe +3 more
core +3 more sources
Asian Journal of Control, EarlyView.Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley +1 more source
, 2012 Modern technologies are producing a wealth of data with complex structures. For instance, in two-dimensional digital imaging, flow cytometry, and electroencephalography, matrix type covariates frequently arise when measurements are obtained for each ...
Li, Lexin, Zhou, Hua
core +1 more source