Results 71 to 80 of about 6,488 (205)
Assessing Influence on Partially Varying-coefficient Generalized Linear Model
Revstat Statistical JournalIn this paper we discuss estimation and diagnostic procedures in partially varying-coefficient generalized linear models based in the penalized likelihood function.
Germán Ibacache-Pulgar +2 more
doaj +1 more source
International Journal of Mathematics and Mathematical Sciences, 2005 We construct a number of semiparametric duality models and establish appropriate duality results under various generalized (ℱ,b,ϕ,ρ,θ)-univexity assumptions for a multiobjective fractional subset programming problem.
G. J. Zalmai
doaj +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
International Journal of Preventive Medicine, 2012 Background: The goal of this study is to extend the applications of parametric survival models so that they include cases in which accelerated failure time (AFT) assumption is not satisfied, and examine parametric and semiparametric models under ...
Alireza Abadi +3 more
doaj
Henderson's method approach to Kernel prediction in partially linear mixed models
Cumhuriyet Science Journal, 2020 In this article, we propose Kernel prediction in partially linear mixed models by using Henderson's method approach. We derive the Kernel estimator and the Kernel predictor via the mixed model equations (MMEs) of Henderson's that they give the best ...
Seçil Yalaz, Özge Kuran
doaj +1 more source
Parametric Time‐Variation in the Unconditional Volatility: Estimation and Inference
Journal of Time Series Analysis, EarlyView.ABSTRACT We propose modeling time‐variation in the unconditional volatility by augmenting the standard GARCH model by a deterministic time‐varying intercept. The model, called the additive time‐varying (ATV‐)GARCH model, can be interpreted as a reduced form of a model including covariates and can be derived from a multiplicative decomposition of ...
Niklas Ahlgren +2 more
wiley +1 more source
A semiparametric changepoint model [PDF]
Biometrika, 2004 Summary: A semiparametric changepoint model is considered and the empirical likelihood method is applied to detect the change from a distribution to a weighted distribution in a sequence of independent random variables. The maximum likelihood changepoint estimator is shown to be consistent.
openaire +2 more sources
Behavioral Charity: Third‐Party Ratings of Nonprofits as Salience and Heuristics
Public Administration Review, EarlyView.ABSTRACT Financial disclosure through tax returns is the primary regulatory mechanism for holding nonprofits accountable to donors in the USA. The assumption that donors will make rational decisions using disclosed information when giving to nonprofits is central to this regulation. But what if they rely on mental shortcuts instead? This study examines
Ashraf Haque
wiley +1 more source
Characterizing heterogeneity in Alzheimer’s disease progression: a semiparametric model
Scientific ReportsThe progression of Alzheimer’s disease (AD), a leading cause of dementia worldwide, is known for its variability and complexity, challenging the conventional methods of monitoring and predicting disease trajectories.
Fatih Gelir +8 more
doaj +1 more source
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