epiphy (version 0.3.4)

chisq.test: Chi-squared test.

Description

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.

Usage

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<U+2013>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

calpha.test, z.test

Examples

Run this code
# NOT RUN {
# For incidence data:
my_incidence <- incidence(tobacco_viruses)
my_fisher <- agg_index(my_incidence, method = "fisher")
chisq.test(my_fisher)

# }

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