HC | R Documentation |
This function calculates the covariance structure for heteroskedasticity linear regression model.
HC(model, method=4, k=0.7)
model |
Any object of class |
method |
Method HC that will be used to estimate the covariance structure. The argument |
k |
Constant used by the method HC5. The suggestion of the authors is to use |
Returns an object of class matrix
with the estimated covariance matrix.
Pedro Rafael Diniz Marinho <pedro.rafael.marinho@gmail.com>
Cribari-Neto, F. (2004). Asymptotic inference under heteroskedasticity of unknown form. Computational Statistics and Data Analysis, 45, 215-233.
Cribari-Neto, F.; Souza, T.C.; Vasconcellos, K.L.P. (2007). Inference under heteros- kedasticity and leveraged data. Communications in Statistics, Theory and Methods, 36, 1877-1888. [Errata: 37, 2008, 3329-3330.]
Horn, S.D.; Horn, R.A.; Duncan, D.B. (1975). Estimating heteroskedastic variances in linear models. Journal of the American Statistical Association, 70, 380-385.
MacKinnon, J.G.; White, H. (1985). Some heteroskedasticity-consistent covariance matrix estimators with improved finite-sample properties. Journal of Econometrics, 29, 305-325.
White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817-838.
data(schools)
datas = schools[-50L,]
y = datas$Expenditure
x = datas$Income/10000
model = lm(y ~ x)
HC(model, method=4)
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