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Variable selection in semiparametric regression modeling
The Annals of Statistics, 2008 In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and selection of significant variables for the parametric portion.
Li, Runze, Liang, Hua
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Journal of Forecasting, Volume 45, Issue 4, Page 1529-1558, July 2026.ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio +1 more
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Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation. [PDF]
Lifetime Data Anal, 2023 Wong KY, Zhou Q, Hu T.
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Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach
Journal of Forecasting, Volume 45, Issue 4, Page 1985-2000, July 2026.ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch +3 more
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Semiparametric regression on cumulative incidence function with interval-censored competing risks data and missing event types. [PDF]
Biostatistics, 2022 Park J +3 more
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Statistics in Medicine, Volume 45, Issue 15-17, July 2026.ABSTRACT The human microbiome plays a crucial role in health, but understanding its dynamic relationship with the host requires regular monitoring. Beyond challenges such as high dimensionality and sparsity, additional complexities arise, particularly within‐cluster correlation from repeated measures and pervasive missing data. To address these issues,
Jinyuan Liu +10 more
wiley +1 more source
Estimating equivalence scales and non-food needs in Egypt: Parametric and semiparametric regression modeling. [PDF]
PLoS One, 2021 Awwad FA, Abdel-Rahman S, Abonazel MR.
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Estimation of a semiparametric mixture of regressions model [PDF]
Journal of Nonparametric Statistics, 2013 We introduce in this paper a new mixture of regressions model which is a generalisation of the semiparametric two-component mixture model studied in Bordes, Delmas, and Vandekerkhove [(2006b), ‘Semiparametric Estimation of a Two-component Mixture Model When a Component is Known’, Scandinavian Journal of Statistics, 33, 733–752].
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Strategic Management Journal, Volume 47, Issue 7, Page 1935-1979, July 2026.Abstract Research Summary We adopt a network‐based perspective to examine the effects of hiring strategies in terms of the diversity of hiring sources. Considering the transferability of general and firm‐specific skills, we propose that firms can reduce integration costs while gaining diversity benefits when they hire from a focused set of firms that ...
Sang Won Han, Shinjae Won
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Econometrics at the Extreme: From Quantile Regression to QFAVAR1
Journal of Economic Surveys, Volume 40, Issue 3, Page 1672-1686, July 2026.ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source