Description Usage Arguments Details Value References See Also Examples
Kolmogorov-Smirnov test providing a comparison of a fitted distribution with the empirical distribution.
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x |
a numeric vector of data values |
distn |
character string naming the null distribution |
fit |
list of null distribution parameters |
H |
a treshold value |
alternative |
indicates the alternative hypothesis and must be one of "two.sided" (default), "less", or "greater". Initial letter must be specified only. |
sim |
maximum number of szenarios in the Monte-Carlo simulation |
tol |
if the difference of two subsequent p-value calculations is lower than |
estfun |
an function as character string or |
The Kolmogorov-Smirnov test compares the null distribution with the empirical distribution function of the observed data, where left truncated data samples are allowed. The test statistic is given by
KS+ = sqrt(n)/(1-zH) sup(zH + j/n (1-zH) -zj)
KS+ = sqrt(n)/(1-zH) sup(zj - (zH + (j-1)/n (1-zH)))
KS = max(KS+, KS-)
with z_H = F_theta(H) and z_j=F_theta(x_j), where x_1, …, x_n are the ordered data values. Here, F_theta is the null distribution.
A list with class "mchtest" containing the following components
statistic |
the value of the Kolmogorov-Smirnov statistic |
treshold |
the treshold value |
p.value |
the p-value of the test |
data.name |
a character string giving the name of the data |
method |
the character string "Kolmorov-Smirnov test" |
alternative |
the alternative |
sim.no |
number of simulated szenarios in the Monte-Carlo simulation |
Chernobay, A., Rachev, S., Fabozzi, F. (2005), Composites goodness-of-fit tests for left-truncated loss samples, Tech. rep., University of Calivornia Santa Barbara
ad.test, v.test, adup.test
for other supremum class tests and ad2.test, ad2up.test,
w2.test for quadratic class tests. For more details see mctest.
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