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This repository has been archived by the owner on Dec 3, 2019. It is now read-only.
I am unsure if this package is the right place to implement these, but wanted to ask. For robust variance covariance estimators sometimes kernels are implemented to account for spatial or temporal correlation of an assumed or estimated form (Heteroscedastic and Autocorrelation Consistent / HAC variance covariance estimators). Would this package be a good place to have these kernels implemented? Here is a reference of the R implementation of these Sandwich and here is another implementation in Julia CovarianceMatrices.jl.
The text was updated successfully, but these errors were encountered:
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I am unsure if this package is the right place to implement these, but wanted to ask. For robust variance covariance estimators sometimes kernels are implemented to account for spatial or temporal correlation of an assumed or estimated form (Heteroscedastic and Autocorrelation Consistent / HAC variance covariance estimators). Would this package be a good place to have these kernels implemented? Here is a reference of the R implementation of these Sandwich and here is another implementation in Julia CovarianceMatrices.jl.
The text was updated successfully, but these errors were encountered: