Performs z-tests for Fisher's aggregation indices (computed with either count or incidence data).

## Usage

```
z.test(x, ...)
# S3 method for default
z.test(x, ...)
# S3 method for fisher
z.test(
x,
alternative = c("two.sided", "less", "greater"),
conf.level = 0.95,
...
)
```

## Arguments

- x
The output of the

`agg_index`

function with`method = "fisher"`

as parameter.- ...
Not yet implemented.

- alternative
A character string specifying the alternative hypothesis. It must be one of "two.sided" (default), "less" or "greater".

- conf.level
The confidence level of the interval.

## Value

Same kind of object as the one returns by the stats
`chisq.test`

function for example.

## Details

For two-sided tests with a confidence level of 95 the spatial pattern would be random. If z < -1.96 or z > 1.96, it would be uniform or aggregated, respectively.

## References

For count and incidence data:

Moradi-Vajargah M, Golizadeh A, Rafiee-Dastjerdi H, Zalucki MP, Hassanpour M, Naseri B. 2011. Population density and spatial distribution pattern of Hypera postica (Coleoptera: Curculionidae) in Ardabil, Iran. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 39(2): 42-48.

Sun P, Madden LV. 1997. Using a normal approximation to test for the binomial distribution. Biometrical journal, 39(5): 533-544.