"model.matrix", "lm", "glm", "aggregate", "var", "cor", "median")

importFrom("stats", "fitted", "reformulate", "terms", "model.frame", "model.response",

"model.matrix", "lm", "glm", "aggregate", "var", "cor", "median", "setNames",

export(bal.tab, bal.plot, love.plot, f.build, splitfactor,

"as.formula", "relevel", "formula", "update", "delete.response")

if (getRversion() < "3.5.0") importFrom("backports", "...elt", "...length")

importFrom("utils", "combn", "data", "write.csv", "methods")

importFrom("utils", "combn", "data", "write.csv", "methods", "packageDescription")

col_w_mean, col_w_sd, col_w_smd, col_w_vr, col_w_ks, col_w_ovl, col_w_corr)

col_w_mean, col_w_sd, col_w_smd, col_w_vr, col_w_ks, col_w_ovl,

importFrom("utils", "combn", "data", "write.csv", "methods", "packageVersion",

##        ----  TODO: replace the above by calling into splines' package!!
import("SparseM") # need at least as.matrix()
## notably for which we define methods (here, only S3 ones):
## "internal" but hopefully documented properly eventually:
## Don't hide the plot methods on purpose (many surprising args):

##        ----  TODO: replace the above by calling into splines package!!
## NB: Still need 'Depends: SparseM' in DESCRIPTION - as SparseM does not S3export() all

importFrom("graphics", axis, legend, mtext, par, plot, points, lines)
approx, coef, knots, fitted, median, predict, resid, residuals, sd, dnorm,pnorm,
## SR ! -- not yet --> R/SR.R man/conreg.Rd

importFrom("SparseM", as.matrix, as.matrix.csr, solve, t)
approx, coef, knots, fitted, median, predict, resid, residuals, sd,

## Export all names, yes, even .splBasis() etc {all for back-compatibility}:

importFrom(vegan, scores, pasteCall, permutest, envfit, eigenvals)
export(coca, coinertia, corAxis, crossval, rescale)

importFrom(vegan, scores, pasteCall, permutest, envfit, vectorfit,

# this doesn't need to be exported, not sure why, but it works fine
# [1] [.mcmc         as.matrix.mcmc end.mcmc       frequency.mcmc plot.mcmc
# [6] print.mcmc     start.mcmc     summary.mcmc   thin.mcmc      time.mcmc
# [1] [.mcmc.list         as.matrix.mcmc.list as.mcmc.mcmc.list
# [4] end.mcmc.list       plot.mcmc.list      start.mcmc.list
# [7] summary.mcmc.list   thin.mcmc.list      time.mcmc.list
importFrom(stats, start, end, frequency, time, window)