Results 21 to 30 of about 19,234 (259)
An MM Algorithm for the Frailty-Based Illness Death Model with Semi-Competing Risks Data
Mathematics, 2022 For analyzing multiple events data, the illness death model is often used to investigate the covariate–response association for its easy and direct interpretation as well as the flexibility to accommodate the within-subject dependence.
Xifen Huang +4 more
doaj +1 more source
Statistics of Extremes in Athletics
Revstat Statistical Journal, 2011 TV shows on any athletic event make clear that those who want gold medals cannot dispense statistics. And the statistics more appealing to champions and coachers are the extreme order statistics, and in particular maximum (or minimum) values and records.
Lígia Henriques-Rodrigues +2 more
doaj +1 more source
Semi-parametric estimation of shifts
Electronic Journal of Statistics, 2007 Published in at http://dx.doi.org/10.1214/07-EJS026 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Gamboa, Fabrice +2 more
openaire +6 more sources
Mathematics, 2022 We study the non-parametric estimation of partially linear generalized single-index functional models, where the systematic component of the model has a flexible functional semi-parametric form with a general link function.
Mohamed Alahiane +3 more
doaj +1 more source
High Quantile Estimation and the Port Methodology
Revstat Statistical Journal, 2009 In many areas of application, a typical requirement is to estimate a high quantile χ1−p of probability 1−p, a value, high enough, so that the chance of an exceedance of that value is equal to p, small.
Lígia Henriques-Rodrigues +1 more
doaj +1 more source
Gaussian Semi‐parametric Estimation of Fractional Cointegration [PDF]
Journal of Time Series Analysis, 2003 Abstract. We analyse consistent estimation of the memory parameters of a nonstationary fractionally cointegrated vector time series. Assuming that the cointegrating relationship has substantially less memory than the observed series, we show that a multi‐variate Gaussian semi‐parametric estimate, based on initial consistent estimates and possibly ...
openaire +3 more sources
Instrumental Variable Estimation in Semi-Parametric Additive Hazards Models [PDF]
Biometrics, 2018 Summary Instrumental variable methods allow unbiased estimation in the presence of unmeasured confounders when an appropriate instrumental variable is available. Two-stage least-squares and residual inclusion methods have recently been adapted to additive hazard models for censored survival data. The semi-parametric additive hazard model
Matthias Brueckner +2 more
openaire +4 more sources
Minimum-entropy estimation in semi-parametric models [PDF]
Signal Processing, 2005 In regression problems where the density f of the errors is not known, maximum likelihood is unapplicable, and the use of alternative techniques like least squares or robust M-estimation generally implies inefficient estimation of the parameters. The search for adaptive estimators, that is, estimators that remain asymptotically efficient independently ...
Eric Wolsztynski +2 more
openaire +2 more sources
Application of the ADMM Algorithm for a High-Dimensional Partially Linear Model
Mathematics, 2022 This paper focuses on a high-dimensional semi-parametric regression model in which a partially linear model is used for the parametric part and the B-spline basis function approach is used to estimate the unknown function for the non-parametric part ...
Aifen Feng +3 more
doaj +1 more source
Semi-Parametric Estimation in Failure Time Mixture Models [PDF]
Biometrics, 1995 A mixture model is an attractive approach for analyzing failure time data in which there are thought to be two groups of subjects, those who could eventually develop the endpoint and those who could not develop the endpoint. The proposed model is a semi-parametric generalization of the mixture model of Farewell (1982).
openaire +4 more sources