Semi-parametric bivariate polychotomous ordinal regression
Sign Up to like & getrecommendations! Published in 2017 at "Statistics and Computing"
DOI: 10.1007/s11222-015-9622-1
Abstract: A pair of polychotomous random variables $$(Y_1,Y_2)^\top =:{\varvec{Y}}$$(Y1,Y2)⊤=:Y, where each $$Y_j$$Yj has a totally ordered support, is studied within a penalized generalized linear model framework. We deal with a triangular generating process for $${\varvec{Y}}$$Y, a… read more here.
Keywords: ordinal regression; polychotomous ordinal; bivariate polychotomous; model ... See more keywords
Semi-parametric Regression based on Machine Learning Methods for UAS Stall Identification
Sign Up to like & getrecommendations! Published in 2021 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2021.08.355
Abstract: Abstract A semi-parametric regression methodology is formulated to identify the unsteady lift characteristics of a small UAS undergoing dynamic stall. Based on the trailing edge separation model of Leishmann and Beddoes, the nonlinear evolution of… read more here.
Keywords: parametric regression; methodology; machine learning; semi parametric ... See more keywords
A Kernel-Density based Semi-Parametric stochastic degradation model with dependent increments
Sign Up to like & getrecommendations! Published in 2021 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2021.107978
Abstract: Abstract The degradation modeling of highly reliable industrial products is a significant issue for manufacturers, and stochastic process models have been widely applied to model degradation trends. However, they suffer from the two underlying assumptions:… read more here.
Keywords: semi parametric; density; model; degradation increments ... See more keywords
Modern variable selection for longitudinal semi-parametric models with missing data
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2018.1426739
Abstract: ABSTRACT Penalized methods for variable selection such as the Smoothly Clipped Absolute Deviation penalty have been increasingly applied to aid variable section in regression analysis. Much of the literature has focused on parametric models, while… read more here.
Keywords: selection; semi parametric; variable selection; missing data ... See more keywords
Shrinkage estimations of semi-parametric models for high-dimensional data in finite mixture models
Sign Up to like & getrecommendations! Published in 2025 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2025.2453534
Abstract: Abstract This article proposes a novel enhancement to semi-parametric models by integrating shrinkage to improve the predictive accuracy and performance of Ridge and ecpc models. By employing the EM algorithm, updated parameter estimates are derived,… read more here.
Keywords: shrinkage estimations; estimations semi; semi parametric; parametric models ... See more keywords
A general semi-parametric elliptical distribution model for semi-supervised learning
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Nonparametric Statistics"
DOI: 10.1080/10485252.2024.2393725
Abstract: ABSTRACT This research proposes a novel semi-parametric elliptical distribution model for application in semi-supervised learning tasks. We use labelled and unlabelled data to develop a pseudo maximum likelihood method for estimation and classification. The proposed… read more here.
Keywords: elliptical distribution; semi; distribution model; semi supervised ... See more keywords
Bayesian Semi-parametric Design (BSD) for adaptive dose-finding with multiple strata
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Biopharmaceutical Statistics"
DOI: 10.1080/10543406.2020.1730870
Abstract: ABSTRACT In the era of precision medicine, it is of increasing interest to consider multiple strata (e.g. indications, regions, or subgroups) within a single oncology dose-finding study when identifying the maximum tolerated dose (MTD). We… read more here.
Keywords: dose finding; strata; bayesian semi; semi parametric ... See more keywords
Income inequality and environmental quality in China: a semi-parametric analysis applied to provincial panel data
Sign Up to like & getrecommendations! Published in 2020 at "Post-Communist Economies"
DOI: 10.1080/14631377.2020.1793604
Abstract: ABSTRACT This article contributes to the literature on the inequality-environment nexus in China, at the provincial level, by filling three major gaps. First, we enlarge the scope of environmental variables so as to include several… read more here.
Keywords: quality; environmental quality; semi parametric; inequality ... See more keywords
Model-Free Radio Map Estimation in Massive MIMO Systems via Semi-Parametric Gaussian Regression
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2021.3132458
Abstract: Accurate radio maps will be very much needed to provide environmental awareness and effectively manage future wireless networks. Most of the research so far has focused on developing power mapping algorithms for single and omnidirectional… read more here.
Keywords: semi parametric; gaussian regression; parametric gaussian; radio ... See more keywords
On computation of semi-parametric maximum likelihood estimators with shape constraints.
Sign Up to like & getrecommendations! Published in 2020 at "Biometrics"
DOI: 10.1111/biom.13266
Abstract: Large sample theory of semi-parametric models based on maximum likelihood estimation (MLE) with shape constraint on the non-parametric component is well studied. Relatively less attention has been paid to the computational aspect of semi-parametric MLE.… read more here.
Keywords: semi; mle; maximum likelihood; semi parametric ... See more keywords
Semi-Parametric Item Response Theory With O’Sullivan Splines for Item Responses and Response Time
Sign Up to like & getrecommendations! Published in 2025 at "Applied Psychological Measurement"
DOI: 10.1177/01466216251316277
Abstract: Response time (RT) has been an essential resource for supplementing the estimation accuracy of latent traits and item parameters in educational testing. Most item response theory (IRT) approaches are based on parametric RT models. However,… read more here.
Keywords: response time; response theory; response; semi parametric ... See more keywords