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Directional (version 4.0)

Anova for circular data: Analysis of variance for circular data

Description

Analysis of variance for circular data.

Usage

hcf.circaov(u, ina, rads = FALSE)

lr.circaov(u, ina, rads = FALSE)

het.circaov(u, ina, rads = FALSE)

embed.circaov(u, ina, rads = FALSE)

Arguments

u

A numeric vector containing the data.

ina

A numerical or factor variable indicating the group of each value.

rads

If the data are in radians, this should be TRUE and FALSE otherwise.

Value

A vector including:

test

The value of the test statistic.

p-value

The p-value of the test.

kappa

The concentration parameter based on all the data. If the het.circaov is used this argument is not returned.

Details

The high concentration (hcf.circaov), log-likelihood ratio (lr.circaov), embedding approach (embed.circaov) or the non equal concentration parameters approach (het.circaov) is used.

References

Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.

See Also

conc.test, hcf.aov, lr.aov, het.aov, embed.aov

Examples

Run this code
# NOT RUN {
x <- rvonmises(100, 2.4, 15)
ina <- rep(1:4,each = 25)
hcf.circaov(x, ina, rads = TRUE)
lr.circaov(x, ina, rads = TRUE)
het.circaov(x, ina, rads = TRUE)
embed.circaov(x, ina, rads = TRUE)
# }

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