as.data.frame.mefa {mefa} | R Documentation |
The function converts parts of a 'mefa' obect into a data frame.
## S3 method for class 'mefa': as.data.frame(x, ..., fun, name, make.unique = FALSE) mss(x, name, make.unique = FALSE, ...) msr(x, name, make.unique = FALSE, ...) mts(x, name, make.unique = FALSE, ...) mtr(x, name, make.unique = FALSE, ...)
x |
an object of class 'mefa'. |
fun |
a function to determine what to return, see details. It has no default, because the choice is not trivial. |
name |
optional character vector, names to return if not all possible elements are needed, see details. |
make.unique |
logical, useful to use make.unique = TRUE if names to returne are non-unique, dee details. |
... |
other arguments passed to the generic function as.data.frame . |
Four kinds of data frames can be returned, depending on the function used as the fun
argument:
mss
returns summary statistics for samples (richness and abundence) and x$samp
;
msr
returns raw data (x$xtab
) and x$samp
;
mts
returns summary statistics for taxa (occurrence and abundence) and x$taxa
;
mtr
returns raw data (t(x$xtab)
) and x$taxa
.
The name
can be used if only a subset of the summary statistics, or raw data should be returned. The character vector should contain names of elements to return (see examples).
It might (rarely) occur, that names of the summary statistics, or the raw data and the column names of the sample/taxa table overlap (contains names that are common in the two set). In this case, the make.unique = TRUE
can be used to resolve non-uniqueness and avoid the error message produced otherwise.
The functions supplied as the fun
argument can be used separately. Although the usage of the as.data.frame
method is more transparent.
A data frame.
Péter Sólymos, solymos@ualberta.ca
Sólymos P. 2008. mefa: an R package for handling and reporting count data. Community Ecology 9, 125–127.
http://mefa.r-forge.r-project.org/
data(dol.count, dol.samp, dol.taxa) x <- mefa(stcs(dol.count), dol.samp, dol.taxa) ## These two are equivalent as.data.frame(x, fun = mss) mss(x) ## Return only two species as.data.frame(x, fun = msr, c("iiso", "ppyg")) ## Taxa table and summary as.data.frame(x, fun = mts) ## Taxa table and raw data transpose as.data.frame(x, fun = mtr) ## Why is it useful? ## Instead of glm(x$xtab[,"amin"] ~ microhab + method, data = x$samp, family = poisson) ## it is more convenient to use glm(amin ~ microhab + method, data = msr(x), family = poisson)