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Influence Assessment in an Heteroscedastic Errors-in-Variables Model
(TAYLOR & FRANCIS INC, 2012)
The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential ...
Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model
(SPRINGER, 2011)
This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, ...
Weak nondifferential measurement error models
(ELSEVIER SCIENCE BV, 1998)
In this note we consider the class of weak nondifferential measurement error models, which as a special case, contains the class of the nondifferential measurement error models (Carroll et al., 1995). Examples of measurement ...
Influence Assessment in an Heteroscedastic Errors-in-Variables Model
(Taylor and Francis Group, LLCPhiladelphia, 2012)
The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential ...
Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors
(JOHN WILEY & SONS LTD, 2008)
In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone ...
Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model
(TAYLOR & FRANCIS INC, 2009)
Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to ...
The structural Sharpe model under t-distributions
(Taylor & Francis LtdAbingdonInglaterra, 2010)
Bayesian Analysis for Errors in Variables with Changepoint Models
(UNIV NAC COLOMBIA, DEPT ESTADISTICABOGOTA DC, 2012)
Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable ...
Measurement error models with nonconstant covariance matrices
(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2002)
In this paper we consider measurement error models when the observed random vectors are independent and have mean vector and covariance matrix changing with each observation. The asymptotic behavior of the sample mean ...