Internal Functions for perm package: Not to be called by User
These functions are where the algorithms are done. There is much room for improvement in the speed of the exact functions.
ksample.exact.mc(scores, group, nmc = 10^4 - 1, seed = 1234321, digits = 12, p.conf.level = 0.99, setSEED = TRUE) ksample.pclt(scores, group) trend.exact.mc(scores, group, alternative = "two.sided", nmc = 10^3 - 1, seed = 1234321, digits = 12, p.conf.level = 0.99, setSEED = TRUE) trend.pclt(scores, group) twosample.exact.ce(scores, group, cm = NULL, digits = 12) twosample.exact.mc(scores, group, alternative = "two.sided", nmc = 10^4 - 1, seed = 1234321, digits = 12, p.conf.level = 0.99, setSEED = TRUE) twosample.pclt(scores, group) twosample.exact.network(scores, group, digits = 12) getcnt(nodehk, cnt.edge, edgesize)
scores |
vector of response scores |
group |
covariate vector |
alternative |
one of 'less', 'greater', 'two.sided' or 'two.sidedAbs' |
nmc |
number of Monte Carlo replications |
seed |
random number seed |
digits |
digits for rounding of test statistic, equal to that many digits are called tied |
p.conf.level |
confidence level for p-value, used with mc methods |
setSEED |
logical, set to FALSE when performing simulations on mc methods |
cm |
for speed you can input the matrix created from chooseMatrix (see |
nodehk |
nodes for which indeces of arcs are needed |
cnt.edge |
vector of first index for each node |
edgesize |
vector of number of arcs for each node |
Network algorithm is very basic, only works for two group tests. The function getcnt
(called by twosample.exact.network)
gets a vector of indeces representing arcs for set of nodes.
The function getcnt returns
a vector of indeces representing arcs for set of nodes
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