Results 61 to 70 of about 674 (121)

Improving estimation precision through optimal designs and shrinkage methods [Elektronisk resurs]

This thesis book brings together the research findings from four interconnected papers, each contributing to the field of statistical modeling and optimization.
Mandal, Saumen,, Månsson, Kristofer,, Mahmoudi, Akram,, Zeebari, Zangin,, Singull, Martin,   +4 more
core  

Optimal and sequential design for bridge regression with application in organic chemistry

, 2011
This thesis presents and applies methods for the design and analysis of experiments for a family of coefficient shrinkage methods, known collectively as bridge regression, with emphasis on the two special cases of ridge regression and the lasso.
Carnaby, Sarah
core  

A bias-reduced estimator for generalized Poisson regression with application to carbon dioxide emission in Canada. [PDF]

Sci Rep
Alghamdi FM, Gemeay AM, Abd-Elmougod GA, Almetwally EM, El-Qurashi MA, Mekiso GT, Hammad AT.   +6 more
europepmc   +1 more source

Longitudinal Trends in Noncommunicable Disease Risk Factors and Premature Mortality in Saudi Arabia: A 33-Year Ecological Time-Series Study with Machine Learning Prediction. [PDF]

J Clin Med
Alnomasy N, Banappagoudar SB, Alrashedi H, Mahmoud SKM, Abouhashish E, Ruksakulpiwat S.   +5 more
europepmc   +1 more source

Penalized Variable Selection for Joint AFT Random-Effect Model With Clustered Competing-Risks Data. [PDF]

Pharm Stat
Hao L, Do Ha I.
europepmc   +1 more source

Machine Learning-Driven Techno-Economic Uncertainty Analysis in Batch Pharmaceutical Manufacturing. [PDF]

ACS Omega
Ordonez DAR, Costa da Silva Mesquita L, Brandão ALT.   +2 more
europepmc   +1 more source

Development and validation of a multidimensional machine-learning model to predict clinically significant immune-related adverse events in advanced non-small cell lung cancer. [PDF]

Am J Transl Res
Weng X, Zhang H, Huang M.
europepmc   +1 more source

The art of precision in unveiling hydrogen solubility in bines through data-driven modeling. [PDF]

Sci Rep
Hassan R, Kazemi MR.
europepmc   +1 more source

A Machine Learning Framework for the Reconstruction of Composite Fatigue and Fracture Properties: A Synthetic Data Study. [PDF]

Materials (Basel)
Tiwari S, Gupta A.
europepmc   +1 more source

Machine Learning-Enabled Real-Time Prediction of Drying Shrinkage in Fly Ash-Modified Cementitious Materials. [PDF]

ACS Omega
Kupwiwat CT, Prasittisopin L.
europepmc   +1 more source