Usage
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)
Arguments
scores
vector of response scores
alternative
one of 'less', 'greater', 'two.sided' or 'two.sidedAbs'
nmc
number of Monte Carlo replications
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 chooseMatrix). If NULL it is created. 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