Description Usage Arguments Value
an update of compute.cfa that allows one to use other other estimators such as quantile regression or nonparametric methods (not yet implemented) as the first step estimator of the conditional distribution
1 2 3 4 5 6 7 8 9 10 11 12 | compute.cfa2(
tvals,
yvals,
data,
yname,
tname,
xnames = NULL,
method = "dr",
link = "logit",
tau = seq(0.1, 0.99, 0.01),
condDistobj = NULL
)
|
tvals |
the values of the "treatment" to compute parameters of interest for |
yvals |
the values to compute the counterfactual distribution for |
data |
the data.frame where y, t, and x are |
method |
either "dr" or "qr" for distribution regression or quantile regression |
link |
if using distribution regression, any link function that works with the binomial family (e.g. logit (the default), probit, cloglog) |
tau |
if using quantile regression, which values of tau to estimate the conditional quantiles |
condDistobj |
optional conditional distribution object that has been previously computed |
condDist |
optional pre-estimated conditional distribution function |
CFA.OBJ
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