importFrom("stats", "simulate", "variable.names", "model.matrix", "logLik",
"vcov", "AIC", "coef", "confint", "dlogis", "dnorm",
"lm.fit", "plogis", "pnorm", "predict", "qlogis", "qnorm",
"runif", "stepfun", "weights", "approxfun", "xtabs")
export(R, "coef<-", mlt, ctm, confband, Hessian, Gradient)
# Hmlt dmlt, hmlt, pmlt, qmlt, smlt, tmlt

importFrom("graphics", "axis", "box", "lines", "plot")
export(R, "coef<-", mlt, ctm, confband, Hessian, Gradient, as.mlt)

export(R, "coef<-", mlt, ctm, confband, Hessian, Gradient, as.mlt, mltoptim)

export(R, "coef<-", mlt, ctm, confband, Hessian, Gradient, as.mlt,

"runif", "stepfun", "weights", "approxfun", "xtabs", "resid")

"runif", "stepfun", "weights", "approxfun", "xtabs", "resid",

importFrom("Matrix", "Matrix", "colSums", "rowSums", "crossprod")

# Generated by roxygen2: do not edit by hand
export(ml_test)

importFrom("graphics", "axis", "barplot", "hist", "lines", "par",
importFrom("stats", "binomial", "chisq.test", "cor.test", "gaussian",
"glm", "loess", "predict", "qnorm", "quantile", "rbinom",

useDynLib(mmand, .registration = TRUE, .fixes = "C_")

as.uchar, as.char, as.int8, as.uint8, as.int16, as.uint16, as.int24,
# standard post and pre-processing accessors
# methods to handle conversion to internal Ctype

"na.exclude", "pchisq", "pnorm", "rnorm", "var")

importFrom("graphics", "abline", "arrows", "axis", "legend", "par",
importFrom("stats", "dbeta", "density", "median", "optim", "pchisq",

importFrom("stats", "as.formula", "family", "gaussian", "median",

importFrom(graphics, points, axis, abline, par, hist, mtext)
importFrom(stats, optimize, coef, pchisq, weighted.mean, AIC, coefficients, as.formula, formula, quantile, lm, hclust, predict, dist)
importFrom(caroline, groupBy, nerge, m, nv, bestBy)
importFrom(ape, as.phylo, drop.tip, ace, branching.times, is.binary.tree, multi2di, vcv.phylo)
importFrom(caper, comparative.data, pgls, VCV.array, summary.pgls, logLik.pgls)
#importFrom("phytools", "phylosig") # lift via v 0.0-8

importFrom(caroline, m, nv, nerge, bestBy, groupBy)