Results 31 to 40 of about 137 (88)

Bayesian prediction in growth-curve models with correlated errors

Autoregressive model, calibration, correlated errors, Gibbs sampling, growth curves, hicrarchical model, inverse prediction, panel data, prediction, 62F15, 62J05,
Ulrich Menzefricke
core   +1 more source

Parametric modelling of growth curve data: An overview

Alc, BIC, covariance structure, longitudinal data, mean structure, repeated measures, RLRT, 62J05, 62F10, 62P10,
Geert Verbeke, Michael Kenward, Dale Zimmerman, Timothy Gregoire, Jeffrey Hart, Philippe Vieu, Vicente Núñez-Antón, Geert Molenberghs, Mohsen Pourahmadi, Dela Zimmerman, Oliver Schabenberger   +10 more
core   +1 more source

Minimax rate of testing in sparse linear regression

, 2019
International audienceWe consider the problem of testing the hypothesis that the parameter of linear regression model is 0 against an s-sparse alternative separated from 0 in the 2-distance.
Tsybakov, Alexandre, Wang, Yuhao, Carpentier, Alexandra, Collier, Olivier, Comminges, Laëtitia   +4 more
core   +5 more sources

Null intercept measurement error regression models

Maximum likelihood, pretest/posttest data, random effects, 62F05, 62J05,
Julio Singer, Hereno Bolfarine, Reiko Aoki   +2 more
core   +1 more source

Asymptotic efficiency properties of least squares in an ultrastructural model

Measurement errors, direct regression, reverse regression, ultrastructural model, 62J05, 62F12,
Shalabh, A. Srivastava
core   +1 more source

Some equalities for estimations of partial coefficients under a general linear regression model

, 2009
Partitioned linear model, Partial parameters, OLSE, BLUE, Equalities for estimations, Moore-Penrose inverses of matrices, Matrix rank method, 62J05, 62H12,
Yongge Tian, Jieping Zhang
core   +1 more source

Least squares estimators in measurement error models under the balanced loss function

Balanced loss function, direct and reverse regression, ineasurement errors, ultrastructural model, 62J05,
Shalabh
core   +1 more source

On the choice of support of Re-descendingψ-Functions in linear models with asymmetric error distributions

Primary 62F35, secondary 62G05, 62J05, Linear models, asymmetric errors, robust estimation, re-descending influence functions,
M. Hlynka, D. Wiens, J. Sheahan
core   +1 more source

Estimation of regression coefficients subject to exact linear restrictions when some observations are missing and quadratic error balanced loss function is used

Balanced loss function, exact restrictions, missing observations, 62J05,
Shalabh, H. Toutenburg
core   +1 more source

Equality of BLUEs or BLUPs under two linear models using stochastic restrictions

BLUE, BLUP, Generalized inverse, Linear fixed effects model, Linear mixed effects model, Stochastic restrictions, 62J05, 62F10,
Stephen Haslett, Simo Puntanen
core   +1 more source