summary.FDX {FDX}

Summarizing Discrete FDX Results

Description

summary method for class "FDX"

Usage

## S3 method for class 'FDX'
summary(object, ...)

## S3 method for class 'summary.FDX'
print(x, max = NULL, ...)

Arguments

object

an object of class "FDX".

...

further arguments passed to or from other methods.

x

an object of class "summary.FDX".

max

numeric or NULL, specifying the maximal number of rows of the p-value table to be printed. By default, when NULL, getOption("max.print") is used.

Details

summary.FDX objects include all data of an FDX object, but also include an additional table which includes the raw p-values, their indices, the respective critical values (if present), the adjusted p-values (if present) and a logical column to indicate rejection. The table is sorted in ascending order by the raw p-values.

print.summary.FDX simply prints the same output as print.FDX, but also prints the p-value table.

Value

summary.FDX computes and returns a list that includes all the data of an input FDX, plus

Table

a data.frame, sorted by the raw p-values, that contains the indices, that raw p-values themselves, their respective critical values (if present), their adjusted p-values (if present) and a logical column to indicate rejection.

print.summary.FDX returns that object invisibly.

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

# Construction of the p-values and their supports (fisher.pvalues.support
# is from 'DiscreteFDR' package!)
df.formatted <- fisher.pvalues.support(counts = df, input = "noassoc")
raw.pvalues <- df.formatted$raw
pCDFlist <- df.formatted$support

DGR.crit <- DGR(raw.pvalues, pCDFlist, critical.values = TRUE)
DGR.crit.summary <- summary(DGR.crit)
print(DGR.crit.summary)