Results 121 to 130 of about 27,081 (245)
Mixtures of Neural Network Experts With Application to Phytoplankton Flow Cytometry Data
Environmetrics, Volume 37, Issue 7, October 2026.ABSTRACT Flow cytometry is a valuable technique that measures the optical properties of particles at a single‐cell resolution. When deployed in the ocean, flow cytometry allows oceanographers to study different types of photosynthetic microbes called phytoplankton.
Ethan Pawl +3 more
wiley +1 more source
An Analysis of Housing Expenditure Using Semiparametric Cross-Section Models [PDF]
In this paper we model expenditure on housing for owners and renters by means of endogenous switching regression models using cross-section data. We explain the share of housing in total expenditure from family characteristics and total expenditure ...
Charlier, E. +2 more
core
Incremental Propensity Score Interventions: A Primer for Pharmacoepidemiologists
Pharmacoepidemiology and Drug Safety, Volume 35, Issue 10, October 2026.ABSTRACT Background In observational pharmacoepidemiology, estimating average treatment effects (ATEs) is often challenging due to a lack of practical positivity. In highly selective clinical settings, certain patients almost always or never receive treatment, causing ATE estimators to rely on unstable extrapolation.
Byeong Yeob Choi
wiley +1 more source
Efficient estimation of parameters in marginals in semiparametric multivariate models [PDF]
Recent literature on semiparametric copula models focused on the situation when the marginals are specified nonparametrically and the copula function is given a parametric form.
Artem Prokhorov, Valentyn Panchenko
core
Semiparametric latent factor models.
, 2005 We propose a semiparametric model for regression problems involving multiple response variables. The model makes use of a set of Gaussian processes that are linearly mixed to capture dependencies that may exist among the response variables. We propose an efficient approximate inference scheme for this semiparametric model whose complexity is linear in ...
Teh, Yee-Whye +2 more
openaire +4 more sources
Are Neural Representation Learning Methods a Viable Alternative to TMLE for Causal Estimation?
Data Science in Science{Simulation is used to evaluate the performance of deep learning and semiparametric causal estimators under realistic high- and low-dimensional data-generating mechanisms from epidemiologic studies.} Deep learning models that leverage representation ...
Mohammad Ehsanul Karim +1 more
doaj +1 more source
Statistics in Medicine, Volume 45, Issue 23-24, October 2026.ABSTRACT Randomized controlled trials often enroll participants whose characteristics differ from those of a target population. When the distribution of effect modifiers differs between trial participants and the target population, treatment effects estimated within the trial may not be directly applicable to all trial‐eligible individuals.
Lan Wen, Issa J. Dahabreh, Yu‐Han Chiu
wiley +1 more source
Robustness of a semiparametric estimator of a copula [PDF]
Copulas offer a convenient way of modelling multivariate observations and capturing the intrinsic dependence between the components of a multivariate random variable.
Param Silvapulle +2 more
core
Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals [PDF]
This paper considers semiparametric efficient estimation of conditional moment models with possibly nonsmooth residuals in unknown parametric components (theta) and unknown functions (h) of endogenous variables.
Demian Pouzo, Xiaohong Chen
core +2 more sources
A Combined Truncated Spline and Kernel Semiparametric Path Model Development
Cauchy: Jurnal Matematika Murni dan AplikasiSemiparametric path analysis is a combination of parametric and nonparametric path analysis performed when the linearity assumption in some relationships is not met.
Usriatur Rohma +3 more
doaj +1 more source