Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Michael J. Wurm"'
Publikováno v:
Journal of Statistical Software, Vol 99, Iss 1 (2021)
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression m
Externí odkaz:
https://doaj.org/article/e8e3c497a41f4e35934bf2e4130a1e33
Autor:
Michael J, Wurm, Paul J, Rathouz
Publikováno v:
The R journal. 10(1)
This paper introduces a new algorithm to estimate and perform inferences on a recently proposed and developed semiparametric generalized linear model (glm). Rather than selecting a particular parametric exponential family model, such as the Poisson d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::4d63b513e8440ac06c7669aa5b01c977
https://pubmed.ncbi.nlm.nih.gov/30873295
https://pubmed.ncbi.nlm.nih.gov/30873295
Publikováno v:
J Stat Softw
Journal of Statistical Software; Vol 99 (2021); 1-42
Journal of Statistical Software; Vol 99 (2021); 1-42
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::178e6f6037bb21970778a9afaf035be8
Autor:
Michael J. Wurm, Paul J. Rathouz
Publikováno v:
The R Journal. 10:288
This paper introduces a new algorithm to estimate and perform inferences on a recently proposed and developed semiparametric generalized linear model (glm). Rather than selecting a particular parametric exponential family model, such as the Poisson d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aac7fa9a287c49420d3e0925ccf1123a
https://doi.org/10.32614/rj-2018-027
https://doi.org/10.32614/rj-2018-027