NAMESPACE

## compiled code
useDynLib(gravy)

## Export

export(GaussPara, HOF, betadiversity, betahill, boxgradient,
gaussgradient, gradscale, hillscale, nichelap, pick.model, plotGrad)

## Do NOT export the following internal functions:

## export(HOF1, gradder.HOF, scale01, ssHOF)

## S3 methods
import(lattice)
importFrom("grDevices", "boxplot.stats")
importFrom("graphics", "abline", "axis", "box", "boxplot", "lines",
           "matlines", "par", "points", "polygon", "rug")
importFrom("stats", "binomial", "coef", "deviance", "df.residual",
           "fitted", "glm", "integrate", "logLik", "median", "nlm",
           "optimize", "plogis", "poisson", "predict", "printCoefmat",
           "qchisq", "qf", "quasibinomial", "residuals", "spline",
           "uniroot", "weighted.mean")

# GaussPara: gravy
S3method(GaussPara, HOF.frame)
S3method(GaussPara, HOF)
S3method(GaussPara, optop.HOF)
S3method(GaussPara, tol.HOF)
# HOF: gravy
S3method(HOF, data.frame)
S3method(HOF, default)
# as.matrix: base
S3method(as.matrix, nichelap.HOF.frame)
# betadiversity: gravy
S3method(betadiversity, HOF.frame)
# coef, deviance, df.residual, fitted, logLik: stats
S3method(coef, HOF)
S3method(deviance, HOF)
S3method(df.residual, HOF)
S3method(fitted, HOF)
S3method(logLik, HOF)
# nichelap: gravy
S3method(nichelap, HOF.frame)
S3method(nichelap, HOF)
# plot: graphics
S3method(plot, HOF.frame)
S3method(plot, HOF)
S3method(plot, betadiversity)
S3method(plot, hillscale)
# predict: stats
S3method(predict, HOF)
# print: base
S3method(print, GaussPara.HOF.frame)
S3method(print, GaussPara.HOF)
S3method(print, HOF.frame)
S3method(print, HOF)
S3method(print, betadiversity)
S3method(print, hillscale)
S3method(print, nichelap.HOF.frame)
# residuals: stats
S3method(residuals, HOF)