Results 131 to 140 of about 58,855 (160)

Bayesian hierarchical modeling and inference for mechanistic systems in industrial hygiene. [PDF]

Ann Work Expo Health
Pan S, Das D, Ramachandran G, Banerjee S.   +3 more
europepmc   +1 more source

Time-dependent prognostic accuracy measures for recurrent event data. [PDF]

Biometrics
Dey R, Schaubel DE, Hanley JA, Saha-Chaudhuri P.   +3 more
europepmc   +1 more source

Distinguishing direct interactions from global epistasis using rank statistics. [PDF]

Proc Natl Acad Sci U S A
Carlson MO, Andrews BL, Simons YB.
europepmc   +1 more source

Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach. [PDF]

Entropy (Basel)
Chen R, Chen Z.
europepmc   +1 more source

Evaluating the Test-Negative Design for COVID-19 Vaccine Effectiveness Using Randomized Trial Data: A Secondary Cross-Protocol Analysis of 5 Randomized Clinical Trials.

JAMA Netw Open
Andrews LIB, Halloran ME, Neuzil KM, van der Laan L, Huang Y, Andriesen J, Patel M, Fisher LH, Janes H, Rouphael N, Walsh SR, Theodore DA, Tieu HV, Sobieszczyk M, El Sahly HM, Baden LR, Falsey AR, Campbell TB, Kelley CF, Healy CM, Immergluck L, Luft B, Hirsch I, de Bruyn G, Truyers C, Priddy F, Sumner KM, Flannery B, Follmann D, Gilbert PB, COVID-19 Prevention Network (CoVPN).   +30 more
europepmc   +1 more source

Trajectories of depressive symptoms and associated factors among reproductive age women in Khwisero, Western Kenya: a longitudinal community-based study

Abajobir A, Sidze E, Janssens W, Aksünger N, Maina D, Gerbaba MJ.   +5 more
europepmc   +1 more source

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Semiparametric Density Deconvolution

Scandinavian Journal of Statistics, 2010
The authors consider density \(f\) estimation by i.i.d. observations with the density \[ g(x)=f*\pi(x)=\int f(x-z)\pi(z)dz, \] where \(\pi\) is a known density of an independent measurement error. The idea is to use a parametric working model \(f(x\,|\,\vartheta)=w(x\,|\,\vartheta)g(x)\), where \(w(x\,|\,\vartheta)\), \(\vartheta\in\Theta\), is a model
Hazelton, M.L., Turlach, B.A.
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Semiparametric efficiency bounds

Journal of Applied Econometrics, 1990
AbstractSemiparametric models are those where the functional form of some components is unknown. Efficiency bounds are of fundamental importance for such models. They provide a guide to estimation methods and give an asymptotic efficiency standard.
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SEMIPARAMETRIC TIME SERIES REGRESSION

Journal of Time Series Analysis, 1994
Abstract.Let (Xi,Yi),i= 0, pL 1,… denote a bivariate stationary time series withXibeing Rd‐valued andYibeing real‐valued. We consider the regression modelYi=θ(Xi) +Zi, where θ(·) is an unknown function and Ziis an autoregressive process. Given a realization of lengthn, we examine the problem of estimating the nonparametric function θ(·) and the ...
Truong, Young K., Stone, Charles J.
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Semiparametric transition rate models

2019
The most widely applied semiparametric model is the proportional hazards model proposed by D. R. Cox, or, as stated in the literature, the Cox model. The Cox model has been used widely, although the proportionality assumption restricts its range of possible empirical applications. This chapter explains the partial likelihood estimation of the model. It
Hans-Peter Blossfeld, Götz Rohwer, Gwendolin J. Blossfeld, Brendan Halpin   +3 more
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