fast.Discrete {DiscreteFDR} | R Documentation |
Fast application of discrete procedures
Description
Apply the [HSU], [HSD], [AHSU] or [AHSD] procedure, without computing the critical constants, to a data set of 2x2 contingency tables using Fisher's exact tests.
Note: In future versions, this function will be removed and replaced by a more flexible one, which will not be limited to Fisher's exact test.
Usage
fast.Discrete(
counts,
alternative = "greater",
input = "noassoc",
alpha = 0.05,
direction = "su",
adaptive = FALSE
)
Arguments
counts |
a data frame of two or four columns and any number of
lines; each line representing a 2x2 contingency table to
test. The number of columns and what they must contain
depend on the value of the |
alternative |
same argument as in fisher.test. The three
possible values are |
input |
the format of the input data frame (see Details section
of fisher.pvalues.support. The three possible values
are |
alpha |
the target FDR level, a number strictly between 0 and 1. |
direction |
a character string specifying whether to conduct a step-up ( |
adaptive |
a boolean specifying whether to conduct an adaptive procedure or not. |
Value
A DiscreteFDR
S3 class object whose elements are:
Rejected |
Rejected raw p-values |
Indices |
Indices of rejected hypotheses |
Num.rejected |
Number of rejections |
Adjusted |
Adjusted p-values (only for step-down direction). |
Method |
Character string describing the used algorithm, e.g. 'Discrete Benjamini-Hochberg procedure (step-up)' |
Signif.level |
Significance level |
Data$raw.pvalues |
The values of |
Data$pCDFlist |
The values of |
Data$data.name |
The variable name of the |
See Also
fisher.pvalues.support, discrete.BH
Examples
X1 <- c(4, 2, 2, 14, 6, 9, 4, 0, 1)
X2 <- c(0, 0, 1, 3, 2, 1, 2, 2, 2)
N1 <- rep(148, 9)
N2 <- rep(132, 9)
Y1 <- N1 - X1
Y2 <- N2 - X2
df <- data.frame(X1, Y1, X2, Y2)
df
DBH.su <- fast.Discrete(counts = df, input = "noassoc", direction = "su")
summary(DBH.su)
DBH.sd <- fast.Discrete(counts = df, input = "noassoc", direction = "sd")
DBH.sd$Adjusted
summary(DBH.sd)
ADBH.su <- fast.Discrete(counts = df, input = "noassoc", direction = "su", adaptive = TRUE)
summary(ADBH.su)
ADBH.sd <- fast.Discrete(counts = df, input = "noassoc", direction = "sd", adaptive = TRUE)
ADBH.sd$Adjusted
summary(ADBH.sd)