| fitstat_register | R Documentation |
Enables the registration of custom fi statistics that can be easily summoned with the function fitstat.
fitstat_register(type, fun, alias = NULL, subtypes = NULL)
type |
A character scalar giving the type-name. |
fun |
A function to be applied to a |
alias |
A (named) character vector. An alias to be used in lieu of the type name in
the display methods (ie when used in |
subtypes |
A character vector giving the name of each element returned by the
function |
If there are several components to the computed statistics (i.e. the function returns
several elements), then using the argument subtypes, giving the names of each of
these components, is mandatory. This is to ensure that the statistic can be used as any
other built-in statistic (and there are too many edge cases impeding automatic deduction).
Laurent Berge
# An estimation
base = iris
names(base) = c("y", "x1", "x2", "x3", "species")
est = feols(y ~ x1 + x2 | species, base)
#
# single valued tests
#
# say you want to add the coefficient of variation of the dependent variable
cv = function(est){
y = model.matrix(est, type = "lhs")
sd(y)/mean(y)
}
# Now we register the routine
fitstat_register("cvy", cv, "Coef. of Variation (dep. var.)")
# now we can summon the registered routine with its type ("cvy")
fitstat(est, "cvy")
#
# Multi valued tests
#
# Let's say you want a Wald test with an heteroskedasticiy robust variance
# First we create the function
hc_wald = function(est){
w = wald(est, keep = "!Intercept", print = FALSE, se = "hetero")
head(w, 4)
}
# This test returns a vector of 4 elements: stat, p, df1 and df2
# Now we register the routine
fitstat_register("hc_wald", hc_wald, "Wald (HC1)", "test2")
# You can access the statistic, as before
fitstat(est, "hc_wald")
# But you can also access the sub elements
fitstat(est, "hc_wald.p")
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