mefa {mefa} | R Documentation |
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.
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, ...)
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. |
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.
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 NA s. |
Peter Solymos, Solymos.Peter@aotk.szie.hu, http://www.univet.hu/users/psolymos/personal/
check.attrib
, marmat
, sscount
, xcount
, xorder
### 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)