# computePValue: P-value In mlincon/pvurt: P-value for augmented Dickey-Fuller unit root test

## Description

Function to approximate the p-value for augmented Dickey-Fuller test.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17``` ```computePValue(object, ...) ## S3 method for class 'numeric' computePValue(object, n, type = c("nc", "c", "ct"), model = c("gam", "poly"), d = NULL, ...) ## S3 method for class 'fHTEST' computePValue(object, model = c("gam", "poly"), type = c("nc", "c", "ct"), d = NULL, ...) ## S3 method for class 'ur.df' computePValue(object, model = c("gam", "poly"), d = NULL, ...) ## S3 method for class 'htest' computePValue(object, model = c("gam", "poly"), d = NULL, ...) ```

## Arguments

 `object` Numeric value or an object (`fHTEST`, `ur.df` or `htest`) for which p-value needs to approximated. `...` Further arguments passed to methods. `n` Sample size. `type` The type of unit root test. Currently supports: `nc` for test without drift and trend, `c` for test with only drift and `ct` for test with both drift and trend. `model` The model type to be used for approximation. Available is GAM and polynomial regression. If `gam` is chosen, then `d` has no effect. `d` The degree for polynomial. `d` must be ≥ 3 and ≤ 6. If `gam` is chosen, then `d` has no effect.

## Details

Based on the chosen model (GAM or polynomial), the function returns the approximated p-value. Default is GAM model.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```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") ```

mlincon/pvurt documentation built on June 8, 2021, 4:14 p.m.