Description Usage Arguments Details Value Author(s) References Examples
Performs Spiegelhalter test for the composite hypothesis of normality, see Spiegelhalter (1977).
1 | spiegelhalter.norm.test(x, nrepl=2000)
|
x |
a numeric vector of data values. |
nrepl |
the number of replications in Monte Carlo simulation. |
The Spiegelhalter test for normality is based on the following statistic:
T = ≤ft( (c_nu)^{-(n-1)}+g^{-(n-1)} \right)^{1/(n-1)},
where
u=\frac{X_{(n)}-X_{(1)}}{s}, \quad g=\frac{∑_{i=1}^n|X_i-\overline{X}|}{s√{n(n-1)}}, \quad c_n=\frac{(n!)^{1/(n-1)}}{2n}, \quad s^2=\frac{1}{n-1}∑_{i=1}^n(X_i-\overline{X})^2.
The p-value is computed by Monte Carlo simulation.
A list with class "htest" containing the following components:
statistic |
the value of the Geary statistic. |
p.value |
the p-value for the test. |
method |
the character string "Spiegelhalter test for normality". |
data.name |
a character string giving the name(s) of the data. |
Ilya Gavrilov and Ruslan Pusev
Spiegelhalter, D. J. (1977): A test for normality against symmetric alternatives. — Biometrika, vol. 64, pp. 415–418.
1 2 | spiegelhalter.norm.test(rnorm(100))
spiegelhalter.norm.test(rexp(100))
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