README.md

In Kaique-fhs/Error: Model with errors in variables

MEV {Error} Package for R

Regression in model with errors

Description

The Error package has the MEV function that can be used to adjust models with variable errors. It can be used to perform regressions on variables that have measurement errors.

How to install

install.packages("devtools")
library(devtools)

install_github("Kaique-fhs/Error")
library(Error)

Usage

MEV(x, y, lambda_x, Correction = FALSE, method = "Bartlett",
  beta_til = 0, conf.level = 0.95, ...)

Arguments

• x Values vector
• y Error vector
• lambda_x Ratio of variances between values and error
• Correction Small sample correction, use TRUE or FALSE
• method The correction method that will be considered "Bartlett", "B1" or "B2"
• beta_til Parameter value to be tested
• conf.level Significance level for the hypothesis test
• ... Not always use all arguments

Details

Only use the conf.level, beta_til e method arguments when running equals "Y", otherwise these arguments will not affect the results.

Author(s)

Kaíque Ferreira Henrique de Souza

Dra. Tatiane Ferreira do N. M. da Silva

References

Aoki, R., Bolfarine, H. e Singer, J.M. (2001). Null intercept measurement error regressionmodels.TestA, 10, 441-457.

Aubin, E.C.Q. e Cordeiro, G.M. (2000). Bartlett-corrected tests for normal linear modelswhen the error covariance matrix is nonscalar.Communications in Statistics, Theory andMethods,29, 2405-2426.

Barndorff–Nielsen, O.E. (1986), Inference on full or partial parameters, based on the stan-dardized signed log likelihood ratio,Biometrika, 73, 307-322.

Bartlett, M.S. (1937), Properties of sufficiency and statistical tests,Proceedings of RoyalSociety of London A, 160, 268-282.

Bayer, F.M., Cribari–Neto, F. (2013). Bartlett corrections in beta regression models.Journalof Statistical Planning and Inference, 143, 531–547.

Botter, D.A. e Cordeiro G.M. (1997). Bartlett corrections for generalized linear models withdispersion covariates.Communications in Statistics, Theory and Methods, 26, 279-307.

Chan, L.K.&Mak, T.K., On the maximum likelihood estimation of a linear structuralrelashionship when the intercept is known,Journal of Multivariate Analysis, 9, 304-313(1979).

Fuller, S. (1987),Measurement Error Models. Wiley, New York.

Melo, T.F.N., Vasconcellos, K.L.P., Lemonte, A.J. (2009). Some restriction tests in a newclass of regression models for proportions.Computational Statistics and Data Analysis, 53,3972–3979.

See Also

lm

Examples

x = seq(1,100,length.out = 100)
y = sort(runif(100,1,10))

MEV(x, y, lambda_x = 2 )
MEV(x, y, lambda_x = 1, beta_til = 4 ,conf.level = 0.95 ,Correction = TRUE)

Kaique-fhs/Error documentation built on June 6, 2023, 4:43 p.m.