evaluate_residuals: Evaluate if the dats is consistent with white noise

In josephsdavid/tswgewrapped: Helpful wrappers for 'tswge', 'vars' and 'nnfor' time series packages

Description

Evaluate if the dats is consistent with white noise

Usage

evaluate_residuals(
  x,
  p = 0,
  q = 0,
  k_val = c(24, 48),
  alpha = 0.05,
  lag.max = 50,
  model_name = "My Model"
)

Arguments

x	the time series
p	the ar order (Default = 0)
q	the ma order (Default = 0)
k_val	a vector of k values for ljung_box test
alpha	Significance level to be used for ljung_box tests
lag.max	Value of lags to plot for the ACF (Default: 50)
model_name	Model name or identifier (Default: "My Model")

Value

the results of the tests, in tidy data format

Examples

library(tswge)

# Generated White Noise 
wn = gen.arma.wge(n = 200, sn = 101)
evaluate_residuals(wn)

# Not White Noise
data(hadley) 
evaluate_residuals(hadley)

josephsdavid/tswgewrapped documentation built on July 31, 2020, 9:36 a.m.