knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )

This package has been created as part of my master thesis. The package has only one user facing function: `computePVale()`, which approximates p-value (cumulative probability) for augmented Dickey-Fuller unit root test based on the distribution of the test statistics. The approximation is based on pre-trained generalized additive logistic model or logistic regression with polynomial terms.

The function can take either a numeric value or the output from the four functions of the following three packages: `adfTest()` and `unitrootTest()` from `fUnitRoots`, `adf.test()` from `tseries` and, lastly, `ur.df()` from `urca`. If output from any of the function is passed on, `computePVale()` appends its approximation result to the original output.

The package has not been released in CRAN. To install use:

devtools::install_github("mlincon/pvurt")

Since the package must be complied, ensure that `Rtools.exe` is installed beforehand.

library(pvurt) y <- arima.sim(model = list(order = c(0, 1, 0)), n = 100) # Test type: with drift and trend # package: fUnitRoots library(fUnitRoots) computePValue(adfTest(y, lags = 3, type = "ct")) computePValue(unitrootTest(y, lags = 3, type = "ct")) # package: urca library(urca) computePValue(ur.df(y, lags = 3, type = "trend")) # print summary summary(computePValue(ur.df(y, lags = 3, type = "trend"))) # package: tseries library(tseries) computePValue(adf.test(y, alternative = "stationary", k = 3)) # no packages tStat <- -2.239 sampleSize <- 100 computePValue(tStat, n = sampleSize, model = "gam", type = "ct")

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