# Fidelity and frequency of species in clusters Calculates the fidelity of species to clusters. Returns equalized phi coefficients of association, an ordered frequency table and Fisher`s exact test for the probability of obtaining the observed frequencies. Isopam objects as well as other combinations of tables and cluster vectors are accepted as input data. An associated plotting method visualises how closely individual species are associated with clusters. UTF-8 1.1 ```r isotab(x, level = NULL, clusters = NULL, phi.min = "isotab", p.max = .05) ## S3 method for class 'isotab' print(x, n = NA, ...) ``` ## Arguments - `x`: Object either of class `isopam` or a dataframe or matrix with rownames (plot names) and column names (species names) that is accompanied by a cluster vector (`clusters`) with named elements corresponding to the rows in `x`. Tibbles need a column with plot names (), while the other columns are of class or . In method `print`, `x` is an object of class `isotab`. - `clusters`: Vector with assignments of clusters to plots, only needed if `x` is not an isopam object. The names of the elements need to be identical to the rownames of `x`. - `level`: Level in cluster hierarchy starting with 1 = first division. - `phi.min`: Threshold of equalized **phi** determining which species are listed in the upper part of the table. Applies only to species passing the criterion defined by `p.max`. If `phi.min = "isopam"` (the default) isotab suggests a value based on the numbers of observations. - `p.max`: Threshold of Fisher's **p** determining which species are listed in the upper part of the table. Applies only to species passing the criterion defined by `phi.min`. - `n`: number of lines used by `print`. If `NA` (the default), n is oriented on the number of diagnosic species. Use `n = Inf` to print all rows. - `...`: other arguments used by `print`. ## Details `phi.min` is based on the 'equalized **phi**' value according to & 2006. The threshold proposed if `phi.min` is set to "isotab" should be adjusted to local conditions. The significance (Fisher's **p**) refers to the probability that the observed frequency is reached. The test is two-tailed, which means that exceptionally low frequencies can result as highly significant as well as exceptionally high frequencies. This allows positive and negative characterisation of a cluster by species. ## Returns - **call**: generating call - **depth**: Number of levels in the cluster hierarchy from the original clustering procedure. - **level**: Level chosen for isotab. - **tab**: Ordered species by cluster table with frequencies and their significance. The latter is derived from Fisher's exact test (see `fisher_p` and details, **p** <= 0.05: *, **p** <= 0.01: **, **p** <= 0.001: ***). - **phi**: Dataframe with equalized phi values (see details). - **fisher_p**: Numerical results from Fisher's exact test (see details) - **n**: Matrix with cluster sizes. - **thresholds**: `phi.min` and `p.max` used for table sorting. - **typical**: Text with items (often species) typically found in clusters (according to `thresholds`). - **typical_vector**: `typical` as a single character vector. - **sorted_table**: Ordered species by plot table. ## References , L., , M. (2006): Statistical determination of diagnostic species for site groups of unequal size. **Journal of Vegetation Science** 17 : 809-–818. Schmidtlein, S., , L., Feilhauer, H., Faude, U. (2010): A brute force approach to vegetation classification. **Journal of Vegetation Science** 21 : 1162--1171. ## Author(s) Sebastian Schmidtlein ## See Also `isopam`, `plot.isotab` ## Examples ```r ## load data to the current environment data(andechs) ## call isopam with the standard options ip <-isopam(andechs) ## build table it <- isotab(ip) it ## change phi threshold it <- isotab(ip, phi.min = 0.8) ## switch cluster level it <- isotab(ip, level = 1) it ```

isotab function