A character string describing the method for the p-value calculation of the runs
test.
"exact" chooses the calculation via exact distribution of the # of runs. "normal" denotes the normal approximation like the function(s) runs.test()
of the packages tseries or lawstat. "cc" chooses the continuity correction to the large sample approximation
like in the statistical software SPSS.
Details
This function calculates the 2-sided p-value of the runs.test.
The large sample approximations are an adaption from the codes for runs.test()
found in the R-packages lawstat and tseries.
The aim of this own was to avoid the heavy footprint of both packages for this small
package.
The user can choose the application of a continuity correction to the normal
approximation like a SAS implementation http://support.sas.com/kb/33/092.html uses
or like SPSS if n<50.
The exact distribution of runs and the p-value based on it are described in the manual
of SPSS "Exact tests" to be found f.i. http://www.sussex.ac.uk/its/pdfs/SPSS_Exact_Tests_21.pdf.
If pmethod="exact" is chosen and n>30 and n1>12 and n2>12 (see pruns.exact)
the continuity corrected version of the normal approximation is used to save time and memory.
Value
Numeric p-value of the 2-sided test.
Author(s)
D. Labes
adapted from runs.test() package lawstat
Authors: Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao
and from runs.test() package tseries
Author: A. Trapletti
See Also
pruns.exact
Examples
# alternating sequence 1,2,1,2 ...
# maybe seen as numeric representation of 'TR','RT' ...
# and is used in that way here in this package
x <- rep(c(1, 2), 6)
runs.pvalue(x, pmethod="normal")
# should give 0.002464631
# exact p-value
runs.pvalue(x, pmethod="exact")
# should give 0.004329004
#
# same for 3 numbers (numeric representation of 3 sequences)
x <- rep(c(1, 2, 3),4)
runs.pvalue(x, pmethod="normal")
# should give 0.2502128
# i.e. is seen as compatible with a random sequence!
# exact p-value, default i.e. must not given exolicitely
runs.pvalue(x)
# should give 0.3212121
# i.e. is seen even more as compatible with a random sequence!