eivknownatt | 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. See Fuller(1987), section 1.1 |
eivknownratue | 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. See Fuller(1987), section 1.3. |
eivknownvaru | 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. See Fuller(1987), section 1.2. |
eivknownvarumod | 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.The theoretical discussion see section 2.5 of Fuller (1987) page 163-172. |
eivlinearinstr | 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. Details see Fuller(1987), page 50-53. |
eivnonlinearinstr | eivnonlinearinstr handle vector-explanatory variable model, which extends the results given by eivlinearinstr. The calculating results are based on moment methods. See Fuller(1987), page 148-151. |
eivplmnor | eivplmnor fits partially linear EIV model where the conditional distribution of y given x and t is normally distributed. The operating procedure is similar with the macro named gplmnoid located in PLM. |
eivtest | eivtest verifies the EIV macros. |
eivvec1 | 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, Sigu are known. All of the variables obey normal distributions. All parameters are estimated by maximum likelihood method in measurement error models, see Fuller W. A. "Measurement Error Models", Wiley and Sons 1987, section 2.2. |
eivvec2 | 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 macro deals with the extension of the model considered in eivknownvaru. see Fuller (1987),page 124-126. |
reca | RECA (REgression CAlibration) is a method in which replacing the unobserved x by its expected value E(x|w,z) and then to perform a standard analysis. |
simex | 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. Details see the 5th and 6th chapters of Carroll, et al.(1995) |