Results 21 to 30 of about 777 (154)
Bayesian Semiparametric Multiple Shrinkage [PDF]
Biometrics, 2010 SummaryHigh‐dimensional and highly correlated data leading to non‐ or weakly identified effects are commonplace. Maximum likelihood will typically fail in such situations and a variety of shrinkage methods have been proposed. Standard techniques, such as ridge regression or the lasso, shrink estimates toward zero, with some approaches allowing ...
MacLehose, Richard F., Dunson, David B.
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A Semiparametric Model for VQTL Mapping [PDF]
Biometrics, 2016 Summary Quantitative trait locus analysis has been used as an important tool to identify markers where the phenotype or quantitative trait is linked with the genotype. Most existing tests for single locus association with quantitative traits aim at the detection of the mean differences across genotypic groups.
Hong, Chuan +4 more
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Semiparametric Wavelet-Based JPEG IV Estimator for Endogenously Truncated Data
IEEE Access, 2019 A new and an enriched JPEG algorithm is provided for identifying redundancies in a sequence of irregular noisy data points which also accommodates a reference-free criterion function.
Nir Billfeld, Moshe Kim
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The Semiparametric Case‐Only Estimator [PDF]
Biometrics, 2010 Summary We propose a semiparametric case‐only estimator of multiplicative gene–environment or gene–gene interactions, under the assumption of conditional independence of the two factors given a vector of potential confounding variables. Our estimator yields valid inferences on the interaction function if either but not necessarily both of two unknown ...
Tchetgen Tchetgen, Eric J. +1 more
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SMALL AREA ESTIMATION OF MEAN YEARS SCHOOL IN KABUPATEN BOGOR USING SEMIPARAMETRIC P-SPLINE
Barekeng, 2022 The Fay-Herriot model, generally uses the EBLUP (Empirical Best Linear Unbiased Prediction) method, is less flexible due to the assumption of linearity.
Christiana Anggraeni Putri +2 more
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Semiparametric Contextual Bandits
CoRR, 2018 This paper studies semiparametric contextual bandits, a generalization of the linear stochastic bandit problem where the reward for an action is modeled as a linear function of known action features confounded by an non-linear action-independent term. We design new algorithms that achieve $\tilde{O}(d\sqrt{T})$ regret over $T$ rounds, when the linear ...
Akshay Krishnamurthy +2 more
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JTAM (Jurnal Teori dan Aplikasi Matematika)Credit risk assessment is crucial for financial institutions to ensure loan repayment. To enhance the prediction accuracy of creditworthiness and timely repayment, this research employs semiparametric structural equation modeling (SEM) to analyze the ...
Fachira Haneinanda Junainto +3 more
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Semiparametric approach to characterize unique gene expression trajectories across time
BMC Genomics, 2006 Background: A semiparametric approach was used to identify groups of cDNAs and genes with distinct expression profiles across time and overcome the limitations of clustering to identify groups.
Southey Bruce R +3 more
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Electronic Journal of Statistics, 2009 We consider the minimax rate of testing (or estimation) of non-linear functionals defined on semiparametric models. Existing methods appear not capable of determining a lower bound on the minimax rate of testing (or estimation) for certain functionals of interest.
Robins, James +3 more
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Generalizing sample tree information with semiparametric and parametric models.
Silva Fennica, 1995 Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model.
Kangas, Annika, Korhonen, Kari
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