mefa {mefa}R Documentation

Makes Object of Class 'mefa'

Description

Makes and object of class 'mefa' from az 'xcont' and sample and species attribute 'xorder' objects. Incomplete 'mea' object can becreated, when one out of samples or species attributes is missing.

Usage

mefa(xc, xorder.samples, xorder.species)

## S3 method for class 'mefa':
print(x, cutoff = 25, ...)

## S3 method for class 'mefa':
plot(x, sample.var = NULL, species.var = NULL, ...)

Arguments

xc object of class 'xcount'.
xorder.samples object of class 'xorder' for sample attributes, or NULL.
xorder.species object of class 'xorder' for species attributes, or NULL.
x an object of class 'mefa'.
sample.var column index (numeric or character) of the sample attribute table to plot as independent variable.
species.var column index (numeric or character) of the species attribute table to plot as independent variable.
cutoff number of samples/species with zero toal count to be listed.
... other arguments.

Details

The plot method works as for 'xcount' objects if only a 'mefa' object is specified. If sample and species attributes (one or both) are also specified, scatterplots or box-and-whiskers diagrams are drawn, based on the type of the independent variable. Species richness, number of individuals, abundance and number of species occurrences are plotted as response variable. If the crosstable is binary, only richness and occurences are used.

Value

A result is an object of class 'mefa'.

data count data from the 'xcount' object.
sample.attr data frame containing data of 'xorder' object containing sample attributes.
species.attr data frame containing data of 'xorder' object containing species attributes.
call returns the call.
segment segment of the 'xcount' object.
digits digits of the 'xcount' object.
nsamples number of rows (samples) in data.
nspecies number of columns (species) in data.
totalcount sum of count or measurement in data.
presences sum of presences in data.
ninds a vector, containing number of individuals (or sum of measurement values) within samples.
srichn a vector, containing number of species (based on occurences) within samples.
specabund a vector, containing number of individuals (or sum of measurement values) within species.
specoccur a vector, containing number of occurences within species.
attributes character, indicating the presence of "both" or only one ("samples.only" or "species.only") attribute tables.
attrib.matrix a matrix with 2 rows and 3 columns. Columns contain check.setrel, number of variables and na from 'xcount' objects for samples (first row) and species (second row). If one 'xorder' object is missing, respective row contains NAs.

Author(s)

Peter Solymos, Solymos.Peter@aotk.szie.hu, http://www.univet.hu/users/psolymos/personal/

See Also

check.attrib, marmat, sscount, xcount, xorder

Examples

### Example 1: simple atrificial data

ss <- data.frame(
cbind(
c("sample1","sample1","sample2","sample2","sample3","sample4"),
c("species1","species1","species1","species2","species3","zero.count"),
c("male","female","male","female","male","male")
),
c(1, 2, 10, 3, 4, 1)
)
colnames(ss) <- c("sample.id", "species.id", "gender", "catch")

spectab <- as.data.frame(rbind(
        c("species3", "family1", "1"),
        c("species2", "family2", "5"),
        c("species1", "family1", "2"),
        c("species5", "family2", "1"),
        c("species4", "family1", "10")
))
colnames(spectab) <- c("species", "taxonomy", "size")

sampletab <- as.data.frame(rbind(
        c("sample3", "bad"),
        c("sample1", "good"),
        c("sample2", "good"),
        c("sample4", "bad")))
colnames(sampletab) <- c("sample", "quality")

xct <- xcount(sscount(ss, zc="zero.count"))
xo1 <- xorder(xct, "samples", sampletab, 1)
xo2 <- xorder(xct, "species", spectab, 1)

mf1 <- mefa (xct, xo1, xo2)
mf1

mf2 <- mefa(xcount(sscount(ss, zc="zero.count"), 2), xo1, xo2)
mf2

### Example 2: field data of Villany Hills

## Not run: 
data(landsnail, vsample, vtable)

vt <- as.xcount(vtable, FALSE)
spec <- xorder(vt, which="species", landsnail, 2)
sampl <- xorder(vt, which="samples", vsample, 1)

vmf <- mefa(vt, sampl, spec)
vmf

plot(vmf)
plot(vmf,type="rank")
plot(vmf, 3)
plot(vmf, NULL, 5)
plot(vmf, "site.descr", "shell.dimension")

### Example 3: field data of the dolina

data(dol.count, dol.sample, landsnail)

dmf <- mefa(
dxc <- xcount(sscount(fill.count(dol.count), zc="zero.count")),
xorder(dxc, which="samples", dol.sample, 1),
xorder(dxc, which="species", landsnail, 2)
)

dmf

plot(dmf, "microhabitat", "shell.dimension")
## End(Not run)

[Package mefa version 1.1-0 Index]