Performs chi-squared tests for Fisher's aggregation indices (computed with
either count or incidence data). If another kind of data is provided, the R
standard `chisq.test`

function is called.

chisq.test(x, ...)
# S3 method for default
chisq.test(x, ...)
# S3 method for fisher
chisq.test(x, ...)

## Arguments

x |
Either the output of the `agg_index` function with
`method = "fisher"` as parameter, or another R object. In the latter
case, stats::`chisq.test` is called. |

... |
Further arguments to be passed to
stats::`chisq.test` . |

## Details

Under the null hypothesis for Fisher's aggregation index (index = 1, i.e. a
random pattern is observed), (N - 1)*index follows a chi-squared distribution
with N - 1 degrees of freedom. N is the number of sampling units.

## References

For count and incidence data:

Madden LV, Hughes G. 1995. Plant disease incidence: Distributions,
heterogeneity, and temporal analysis. Annual Review of Phytopathology 33(1):
529–564.
doi:10.1146/annurev.py.33.090195.002525

Patil GP, Stiteler WM. 1973. Concepts of aggregation and their
quantification: a critical review with some new results and applications.
Researches on Population Ecology, 15(1): 238-254.

## See also

## Examples

#>
#> Chi-squared test for (N - 1)*index following a chi-squared
#> distribution (df = N - 1)
#>
#> data: my_fisher
#> X-squared = 232.65, df = 74, p-value < 2.2e-16
#>