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fetwfe().genCoefsCore() and
simulateDataCore() for export, and add tests for them.
(Though these more flexible functions are now available, emphasis for
end users will still be on using wrapper functions
genCoefs() and simulateData().)genCoefs() to a wrapper
function that creates an object that can be piped into
simulateData(), itself a new wrapper function for the
function that was previously called genRandomData(). The
output of simulateData() can then be piped into another new
wrapper function, fetwfeWithSimulatedData().add_ridge to fetwfe(),
which adds a ridge regularization term to the (untransformed)
coefficients in estimation, similarly to the elastic net.getTes() to get treatment effects from a
vector of coefficients generated by genCoefs() and/or
estimated on data generated from genRandomData().genRandomData(), for generating random
panel data suitable for fetwfe(), and
genCoefs(), which generates a random vector of coefficients
that is needed as an input to genRandomData().lambda.max_model_sizemessage()
instead of print(), and modified code so that all messages
are suppressed when the argument verbose is FALSE..Rbuildignore to conform with CRAN
requirements.fetwfe package implementing the
Fused Extended Two-Way Fixed Effects estimator.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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