pFrd | R Documentation |
The method used to compute the P-value is from the reference by Van de Wiel, Bucchianico, and Van der Laan.
pFrd(x,b=NA,trt=NA,method=NA, n.mc=10000)
x |
Either a matrix or a vector containing the data. |
b |
If x is a vector, b is a required vector of block labels. Otherwise, not used. |
trt |
If x is a vector, trt is a required vector of treatment labels. Otherwise, not used. |
method |
Either "Exact", "Monte Carlo" or "Asymptotic", indicating the desired distribution. When method=NA, "Exact" will be used if the number of permutations is 10,000 or less. Otherwise, "Monte Carlo" will be used. |
n.mc |
If method="Monte Carlo", the number of Monte Carlo samples used to estimate the distribution. Otherwise, not used. |
The data entry is intended to be flexible, so that the data can be entered in either of two ways. The following are equivalent:
pFrd(x=matrix(c(1,2,3,4,5,6),ncol=2,byrow=T))
pFrd(x=c(1,2,3,4,5,6),b=c(1,1,2,2,3,3),trt=c(1,2,1,2,1,2))
Returns a list with "NSM3Ch7p" class containing the following components:
k |
number of treatments in the data |
n |
number of blocks in the data |
obs.stat |
the observed D statistic |
p.val |
upper tail P-value |
Grant Schneider
Van de Wiel, M. A., A. Di Bucchianico, and P. Van der Laan. "Symbolic computation and exact distributions of nonparametric test statistics." Journal of the Royal Statistical Society: Series D (The Statistician) 48.4 (1999): 507-516.
Also see the coin
package.
##Hollander-Wolfe-Chicken Example 7.1 Rounding First Base
rounding.times<-matrix(c(5.40, 5.50, 5.55,
5.85, 5.70, 5.75,
5.20, 5.60, 5.50,
5.55, 5.50, 5.40,
5.90, 5.85, 5.70,
5.45, 5.55, 5.60,
5.40, 5.40, 5.35,
5.45, 5.50, 5.35,
5.25, 5.15, 5.00,
5.85, 5.80, 5.70,
5.25, 5.20, 5.10,
5.65, 5.55, 5.45,
5.60, 5.35, 5.45,
5.05, 5.00, 4.95,
5.50, 5.50, 5.40,
5.45, 5.55, 5.50,
5.55, 5.55, 5.35,
5.45, 5.50, 5.55,
5.50, 5.45, 5.25,
5.65, 5.60, 5.40,
5.70, 5.65, 5.55,
6.30, 6.30, 6.25),ncol=3,byrow=TRUE)
#pFrd(rounding.times,n.mc=20000)
pFrd(rounding.times,n.mc=2000)
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