eivknownatt presents the moment estimates of the parameters in the measurement error models, which has only one variable x. The degree of attenuation (also called reliability ratio) is known. All of the variables obey normal distributions.
eivknownratue presents the moment estimates of the parameters in the measurement error models, which has only one variable x. The ratio of two variances of the two measurement errors is known. All of the variables obey normal distributions.
eivknownvaru presents the moment estimates of the parameters in the measurement error models, which has only one variable x. The variance of measurement error sigma_u is known. All of the variables obey normal distributions.
eivknownvarumod presents modified moment estimates of parameters for the measurement error models, which has only one variable x. The variance of measurement error sigma_u is known. All of the variables obey normal distributions.
eivlinearinstr presents the moment estimates of the regression coefficients in the measurement error model with single predictor, which has an instrumental variable W. All of the variables obey normal distributions. All parameters are estimated by moment method in measurement error models.
eivlinearinstrvec handle vector-explanatory variable model, which extends the results given by eivlinearinstr. The calculating results are based on moment methods.
eivvect1 presents the maximum likelihood estimators of the parameters in the measurement error models, which has more than one variable x. The covariances between e and u, Sigeu and the covariance matrix of u, siguu are known. All of the variables obey normal distributions. All parameters are estim
eivvect2 calculates the maximum likelihood estimators of the parameters in the measurement error models when the entire error covariance structure is known or known up to a scalar multiple. This quantlet deals with the extension of the model considered in eivknownvaru.
SIMEX (SIMulation EXtrapolation) is a simulation-based method of estimating and reducing bias due to measurement error. simex is applicable to general estimation methods, for example, least-squares, maximum likelihood, quasi-likelihood, etc.