white_hccme_slow: Calculate the Heteroskedasticity-Consistent Covariance Matrix...
In LeeMorinUCF/aggregress: Regression Analysis with Aggregated Data
Description
Usage
Arguments
Value
See Also
View source: R/aggregress_het.R
Description
white_hccme_slow is a helper function to calculate the HCCME,
to test the calculation for comparison with un-aggregated data, i.e. data
with weights either NULL or equal to 1.
It calculates the covariance matrix from first principles, i.e. with loops.
Usage
1
white_hccme_slow(lm_in)
Arguments
lm_in
is an object of class "lm" that is the output of a
linear regression model.
Value
A list containing two elements. The first is the HCCME covariance
matrix. the second is a data frame of the form of coef(summary(lm_in)),
except with standard errors and the remaining statistics adjusted
for heteroskedasticity.
See Also
white_hccme, which uses vcovHC function in the
sandwich package.
LeeMorinUCF/aggregress documentation built on June 30, 2020, 5:06 a.m.
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Description Usage Arguments Value See Also
View source: R/aggregress_het.R
Description
white_hccme_slow is a helper function to calculate the HCCME,
to test the calculation for comparison with un-aggregated data, i.e. data
with weights either NULL or equal to 1.
It calculates the covariance matrix from first principles, i.e. with loops.
Usage
1 | white_hccme_slow(lm_in)
|
Arguments
lm_in |
is an object of class " |
Value
A list containing two elements. The first is the HCCME covariance
matrix. the second is a data frame of the form of coef(summary(lm_in)),
except with standard errors and the remaining statistics adjusted
for heteroskedasticity.
See Also
white_hccme, which uses vcovHC function in the
sandwich package.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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