ks.test.t {LambertW} | R Documentation |
Performs a two-sided KS test for H_0 that the data comes from a student-t distribution with nu degrees of freedom, mean μ_x, and standard deviation σ_x (not scale!). If the parameters are not specified, the ML estimates given the data are used (see fitdistr
).
ks.test.t(y, theta = NULL)
y |
a numeric vector of data values. |
theta |
parameter vector including the degrees of freedom parameter: theta = (delta, μ_x, σ_x, nu); default: theta = NULL , thus theta is estimated from y . |
This test does not give correct p-values if the parameters are estimated from the data. Future versions will include simulation based p-values. See ks.test
and the references therein (Durbin (1973)).
A list with class "htest" containing the following components:
statistic |
the value of the Kolomogorv-Smirnov statistic. |
p.value |
the p-value for the test. |
alternative |
a character string describing the alternative hypothesis. |
method |
the character string "One-sample Kolmogorov-Smirnov test student-t" plus rounded parameter values. |
data.name |
a character string giving the name(s) of the data. |
Georg M. Goerg