Results 21 to 30 of about 7,325 (196)
Endogeneity in Semiparametric Threshold Regression [PDF]
SSRN Electronic Journal, 2017 This paper estimates threshold regression models with an endogenous threshold variable using a nonparametric control function approach. Assuming diminishing threshold effects, we derive the consistency and limiting distribution of our proposed estimator constructed from the series approximation method for weakly dependent data.
Kourtellos, Andros +2 more
openaire +1 more source
Apstract: Applied Studies in Agribusiness and Commerce, 2017 This paper introduces the semiparametric error correction model for estimation of export-import relationship as an alternative to the least squares approach.
Henry De-Graft Acquah +1 more
doaj +1 more source
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.
openaire +2 more sources
Fitting Nonlinear Structural Equation Models in R with Package nlsem
Journal of Statistical Software, 2017 Structural equation mixture modeling (SEMM) has become a standard procedure in latent variable modeling over the last two decades (Jedidi, Jagpal, and DeSarbo 1997b; Muthén and Shedden 1999; Muthén 2001, 2004; Muthén and Asparouhov 2009).
Nora Umbach +3 more
doaj +1 more source
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
openaire +2 more sources
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
openaire +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
openaire +3 more sources