Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Alan T. K. Wan"'
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 15:679-691
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0acafd461843d57ff5d286ccb33cc10
https://doi.org/10.1002/sam.11598
https://doi.org/10.1002/sam.11598
Publikováno v:
European Journal of Operational Research. 301:772-784
In recent years, model averaging, by which estimates are obtained based on not one single model but a weighted ensemble of models, has received growing attention as an alternative to model selection. To-date, methods for model averaging have been dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f76f7c240296147bd066b8b412458faf
https://doi.org/10.1016/j.ejor.2021.11.015
https://doi.org/10.1016/j.ejor.2021.11.015
Publikováno v:
Canadian Journal of Statistics. 51:630-651
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e235cd66c59c685ce322f5ef138ff438
https://doi.org/10.1002/cjs.11700
https://doi.org/10.1002/cjs.11700
Publikováno v:
Journal of Business & Economic Statistics. 41:157-169
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47402a40b4d650298645a9a9784a2fa4
https://doi.org/10.1080/07350015.2021.2006668
https://doi.org/10.1080/07350015.2021.2006668
Publikováno v:
Journal of the American Statistical Association. 117:495-509
Model average techniques are very useful for model-based prediction. However, most earlier works in this field focused on parametric models and continuous responses. In this article, we study varyi...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d84ed41708e1aca0a015a8523b0b7f28
https://doi.org/10.1080/01621459.2020.1790375
https://doi.org/10.1080/01621459.2020.1790375
Publikováno v:
Econometric Reviews. 39:1100-1124
In recent years, the body of literature on frequentist model averaging in econometrics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad68b17c1d0b9aa77ab998da00b24ec2
https://doi.org/10.1080/07474938.2020.1770995
https://doi.org/10.1080/07474938.2020.1770995
Publikováno v:
Statistics and Its Interface. 13:221-235
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2a58f7b58bf62f5ff8e23c7e9afd103
https://doi.org/10.4310/sii.2020.v13.n2.a7
https://doi.org/10.4310/sii.2020.v13.n2.a7
Publikováno v:
BiometricsREFERENCES.
In this paper, we propose a frequentist model averaging method for quantile regression with high-dimensional covariates. Although research on these subjects has proliferated as separate approaches, no study has considered them in conjunction. Our met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68644b3a9a400a9fe330a9d6f999625d
https://pubmed.ncbi.nlm.nih.gov/34608993
https://pubmed.ncbi.nlm.nih.gov/34608993
Publikováno v:
The international journal of biostatisticsReferences.
Prevalent cohort studies in medical research often give rise to length-biased survival data that require special treatments. The recently proposed varying-coefficient partially linear transformation (VCPLT) model has the virtue of providing a more dy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86c3f45eb351ae581c70643a34f4afa6
https://pubmed.ncbi.nlm.nih.gov/35801995
https://pubmed.ncbi.nlm.nih.gov/35801995
Publikováno v:
Journal of Productivity Analysis. 51:91-103
Model uncertainty is a prominent feature in many applied settings. This is certainty true in the efficiency analysis realm where concerns over the proper distributional specification of the error components of a stochastic frontier model is, generall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::709e16522341b708e987f9347b55b0f9
https://doi.org/10.1007/s11123-019-00547-8
https://doi.org/10.1007/s11123-019-00547-8