| rowFreqs {scrime} | R Documentation |
Computes the frequencies of the levels that the categorical variables in a matrix show.
rowFreqs(x, levels = 1:3, divide.by.n = FALSE, affy = FALSE,
includeNA = FALSE, useNN = c("not", "only", "also"), check = TRUE)
x |
a matrix in which each row represents a categorical variable (e.g., a SNP)
and each column an observation, where the variables are assumed to show the
levels specified by levels. Missing values are allowed in x. |
levels |
vector specifying the levels that the categorical variables in x
show. Ignored if affy = TRUE. |
divide.by.n |
should the numbers of observations showing the respective levels
be divided by the total number of observations, i.e. by ncol(x)? If FALSE,
these numbers are divided by the number of non-missing values of the respective variable.
Ignored if includeNA = TRUE. |
affy |
logical specifying whether the SNPs in x are coded in the Affymetrix
standard way. If TRUE, levels = c("AA", "AB", "BB") and useNN = "also"
will be used (the latter only when includeNA = TRUE). |
includeNA |
should a column be added to the output matrix containing the number of missing values for each variable? |
useNN |
character specifying whether missing values can also be coded by "NN".
If useNN = "not" (default), missing values are assumed to be coded only by NA.
If "only", then missing values are assumed to be coded only by "NN" (and not
by NA. If "both", both "NN" and NA are considered. Ignored
if affy = TRUE. |
check |
should it be checked whether some of the variables show other levels than the one
specified by levels? |
A matrix with the same number of rows as x containing for each variable the numbers
of observations showing the levels specified by levels.
Holger Schwender, holger.schwender@udo.edu
## Not run: # Generate a matrix containing data for 10 categorical # variables with levels 1, 2, 3. mat <- matrix(sample(3, 500, TRUE), 10) rowFreqs(mat) # leads to the same results as rowTables(mat) / ncol(mat) # If mat contains missing values mat[sample(500, 20)] <- NA # then rowFreqs(mat) # leads to the same result as rowTables(mat) / rowSums(!is.na(mat)) ## End(Not run)