Description Usage Arguments Details Value Author(s) References Examples
Performs Hegazy–Green test for the composite hypothesis of normality, see e.g. Hegazy and Green (1975).
1 | hegazy1.norm.test(x, nrepl=2000)
|
x |
a numeric vector of data values. |
nrepl |
the number of replications in Monte Carlo simulation. |
The Hegazy–Green test for normality is based on the following statistic:
T_1 = \frac{1}{n}∑_{i=1}^n{≤ft|Y_{i}-Φ^{-1}{≤ft(\frac{i}{n+1}\right)}\right|},
where
Y_i=\frac{X_{(i)}-\overline{X}}{s}, \quad s^2=\frac{1}{n}∑_{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 Hegazy–Green statistic. |
p.value |
the p-value for the test. |
method |
the character string "Hegazy-Green test for normality". |
data.name |
a character string giving the name(s) of the data. |
Ilya Gavrilov and Ruslan Pusev
Hegazy, Y. A. S. and Green, J. R. (1975): Some new goodness-of-fit tests using order statistics. — Journal of the Royal Statistical Society. Series C (Applied Statistics), vol. 24, pp. 299–308.
1 2 | hegazy1.norm.test(rnorm(100))
hegazy1.norm.test(runif(100,-1,1))
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