setFixest_fml(..., reset = FALSE)

getFixest_fml()

# Small examples with airquality data
data(airquality)
# we set two macro variables
setFixest_fml(..ctrl = ~ Temp + Day,
              ..ctrl_long = ~ poly(Temp, 2) + poly(Day, 2))

# Using the macro in lm with xpd:
lm(xpd(Ozone ~ Wind + ..ctrl), airquality)
lm(xpd(Ozone ~ Wind + ..ctrl_long), airquality)

# You can use the macros without xpd() in fixest estimations
a = feols(Ozone ~ Wind + ..ctrl, airquality)
b = feols(Ozone ~ Wind + ..ctrl_long, airquality)
etable(a, b, keep = "Int|Win")


# Using .[]

base = setNames(iris, c("y", "x1", "x2", "x3", "species"))
i = 2:3
z = "species"
lm(xpd(y ~ x.[2:3] + .[z]), base)

# No xpd() needed in feols
feols(y ~ x.[2:3] + .[z], base)

#
# You can use xpd for stepwise estimations
#

# Note that for stepwise estimations in fixest, you can use
# the stepwise functions: sw, sw0, csw, csw0
# -> see help in feols or in the dedicated vignette

# we want to look at the effect of x1 on y
# controlling for different variables

base = iris
names(base) = c("y", "x1", "x2", "x3", "species")

# We first create a matrix with all possible combinations of variables
my_args = lapply(names(base)[-(1:2)], function(x) c("", x))
(all_combs = as.matrix(do.call("expand.grid", my_args)))

res_all = list()
for(i in 1:nrow(all_combs)){
  res_all[[i]] = feols(xpd(y ~ x1 + ..v, ..v = all_combs[i, ]), base)
}

etable(res_all)
coefplot(res_all, group = list(Species = "^^species"))

#
# You can use macros to grep variables in your data set
#

# Example 1: setting a macro variable globally

data(longley)
setFixest_fml(..many_vars = grep("GNP|ployed", names(longley), value = TRUE))
feols(Armed.Forces ~ Population + ..many_vars, longley)

# Example 2: using ..("regex") to grep the variables "live"

feols(Armed.Forces ~ Population + ..("GNP|ployed"), longley)

# Example 3: same as Ex.2 but without using a fixest estimation

# Here we need to use xpd():
lm(xpd(Armed.Forces ~ Population + ..("GNP|ployed"), data = longley), longley)

#
# You can also put numbers in macros
#

res_all = list()
for(p in 1:3){
  res_all[[p]] = feols(xpd(Ozone ~ Wind + poly(Temp, ..p), ..p = p), airquality)
}

etable(res_all)

#
# lhs and rhs arguments
#

# to create a one sided formula from a character vector
vars = letters[1:5]
xpd(rhs = vars)

# Alternatively, to replace the RHS
xpd(y ~ 1, rhs = vars)

# To create a two sided formula
xpd(lhs = "y", rhs = vars)


#
# Dot square bracket operator
#

# You can create multiple variables at once
xpd(y ~ x.[1:5] + z.[2:3])

# You can summon variables from the environment
var = "a"
xpd(y ~ x.[var])

# ... the variables can be multiple
vars = LETTERS[1:3]
xpd(y ~ x.[vars])

# You can have "complex" variable names but they must be nested in character form
xpd(y ~ .["x.[vars]_sq"])

# DSB can be used within regular expressions
re = c("GNP", "Pop")
xpd(Unemployed ~ ..(".[re]"), data = longley)

# => equivalent to ..("GNP|Pop")