Results 31 to 40 of about 13,851,275 (245)
Mathematics, 2023 Multivariate “Bayesian” regression via a shared component model has gained popularity in recent years, particularly in modeling and mapping the risks associated with multiple diseases.
I. Gede Nyoman Mindra Jaya +5 more
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Penalized Likelihood-Based Estimation of Stratified Semiparametric Cox Models Under Partly Interval Censoring. [PDF]
Biom JABSTRACT In survival data analysis, the stratified Cox model becomes a popular option when the proportional hazards assumption of the conventional Cox model does not hold for certain covariates. For a stratified Cox model, when the observed survival times contain only right censoring, the method of maximum partial likelihood can still be implemented ...
Ma J, Webb A, Manuguerra M, Hudson HM.
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Estimation of a semiparametric transformation model
The Annals of Statistics, 2008 This paper proposes consistent estimators for transformation parameters in semiparametric models. The problem is to find the optimal transformation into the space of models with a predetermined regression structure like additive or multiplicative separability.
Linton, Oliver +2 more
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Semiparametric Additive Beta Regression Models
Revstat Statistical Journal, 2021 In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit ...
Germán Ibacache-Pulgar +2 more
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Robust-BD Estimation and Inference for General Partially Linear Models
Entropy, 2017 The classical quadratic loss for the partially linear model (PLM) and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD)” estimators of both the parametric
Chunming Zhang, Zhengjun Zhang
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Media Statistika, 2020 Confidence interval estimation is important in statistical inference for the parameters of the regression model, but the theory of confidence interval estimation for multi-response semiparametric regression model parameters based on the truncated spline ...
Lilik Hidayati +2 more
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Robust Variable Selection for Single-Index Varying-Coefficient Model with Missing Data in Covariates
Mathematics, 2022 As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health.
Yunquan Song, Yaqi Liu, Hang Su
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A semiparametric model for cluster data
The Annals of Statistics, 2009 In the analysis of cluster data, the regression coefficients are frequently assumed to be the same across all clusters. This hampers the ability to study the varying impacts of factors on each cluster. In this paper, a semiparametric model is introduced to account for varying impacts of factors over clusters by using cluster-level covariates.
Zhang, Wenyang, Fan, Jianqing, Sun, Yan
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Nonparametric and semiparametric estimation with discrete regressors [PDF]
, 1994 This paper presents and discusses procedures for estimating regression curves when regressors are discrete and applies them to semiparametric inference problems.
Delgado, Miguel A., Mora, Juan
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Sparse Semi-Functional Partial Linear Single-Index Regression
Proceedings, 2018 The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure is employed for this task.
Silvia Novo +2 more
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