Description Usage Arguments Details Value Author(s) References See Also Examples
Perform a normality test. The null hypothesis (H0) is that the given data follows a stationary Gaussian process.
1 2  normal.test(y,normality = c("epps","lobato","vavra","rp","jb","ad","shapiro"),
alpha = 0.05)

y 
a numeric vector or an object of the 
normality 
A character string naming the desired test for checking normality. Valid values are

alpha 
Level of the test, possible values range from 0.01 to 0.1. By default 
Several different tests are available:
"lobato"
, "epps"
, "vavras"
and "rp"
test are for testing normality
in stationary process. "jb"
, "ad"
, and "shapiro"
tests are for numeric data.
In all cases, the alternative hypothesis is that y
follows a Gaussian process. By default,
alpha = 0.05
is used to select the more likely hypothesis.
An h.test class with the main results of normal hypothesis test.
Asael Alonzo Matamoros
Epps, T.W. (1987). Testing that a stationary time series is Gaussian. The Annals of Statistic. 15(4), 16831698.
Lobato, I., & Velasco, C. (2004). A simple test of normality in time series. Journal of econometric theory. 20(4), 671689.
Psaradakis, Z. & Vavra, M. (2017). A distance test of normality for a wide class of stationary process. Journal of Econometrics and Statistics. 2, 5060.
NietoReyes, A., CuestaAlbertos, J. & Gamboa, F. (2014). A randomprojection based test of Gaussianity for stationary processes. Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 124141.
Patrick, R. (1982). An extension of Shapiro and Wilk's W test for normality to large samples. Journal of Applied Statistics. 31, 115124.
Cromwell, J. B., Labys, W. C. & Terraza, M. (1994). Univariate Tests for Time Series Models. Sage, Thousand Oaks, CA. 2022.
1 2 3 4 5 6 7 8 9 10 11  # stationary ar process
y = arima.sim(100,model = list(ar = 0.3))
normal.test(y) # epps test
# normal random sample
y = rnorm(100)
normal.test(y,normality = "shapiro")
# exponential random sample
y = rexp(100)
normal.test(y,normality = "ad")

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