export(juliaClassDef) #? or make into class like PythonClassDef?
export( juliaAddToPath, juliaClassDef, juliaGet, juliaImport, juliaUsing, juliaSend, juliaSource )
export(juliaEval, juliaCommand, juliaSerialize, juliaUnserialize, juliaName, juliaPrint, juliaCall)

importFrom(methods, is, allNames, new, callNextMethod)
## Don't export PythonClassDef class for now.
## export(PythonClassDef, PythonFunction, PythonInterface, PythonObject)
## exportClass(PythonClassDef, PythonFunction, PythonInterface, PythonObject)
export(pythonAddToPath, pythonGet, pythonSend, pythonImport, pythonEval, pythonCommand, pythonDefine,
pythonSource, pythonSerialize, pythonUnserialize, pythonName, pythonShell, pythonCall, pythonTask)

importFrom("stats", "quantile", "rnorm", "runif", "dnorm", "integrate", "pnorm", "qnorm")

importFrom("graphics", "legend", "lines", "plot", "title")
importFrom("stats", "integrate", "pnorm", "printCoefmat", "rnorm", "runif")

importFrom("stats", "integrate", "pnorm", "printCoefmat", "rnorm",

importFrom("stats", "is.ts", "loess", "time", "ts.union")

importFrom("graphics", "layout", "legend", "par", "plot", "plot.new", "points")
importFrom("graphics", "persp", "polygon", "segments", "text", "title")

importFrom("stats", "coef", "lm", "median", "na.omit", "optimize","resid", "time")

import(grid, gridExtra, foreign, ggplot2, lattice, reshape2)

exportPattern("^[[:alpha:]]+")
importFrom("stats", "lm", "lm.fit", "optim", "pnorm", "pt", "qlogis", "quantile", "var")

export(fit.zigp, FM, gradient, loglikelihood.zigp, response.zigp, rzigp, wald.test, mle.zigp, optimized.run)

export(fit.zigp, FM, gradient, loglikelihood.zigp, response.zigp, dzigp, pzigp, qzigp, rzigp, wald.test, mle.zigp, optimized.run)

export(fit.zigp, FM, gradient, loglikelihood.zigp, response.zigp, dzigp, pzigp, qzigp, rzigp, wald.test, mle.zigp, optimized.run, vuong)

export(clarke, fit.zigp, FM, gradient, loglikelihood.zigp, response.zigp, dzigp, pzigp, qzigp, rzigp, wald.test, mle.zigp, optimized.run, vuong)

export(clarke, fit.zigp, FM, gradient, loglikelihood.zigp, response.zigp, dzigp, pzigp, qzigp, rzigp, est.zigp, mle.zigp, optimized.run, vuong, eda.od, eda.zi)