smovie (version 1.0.1)

FPearson: Fisher's transformation of the Pearson product moment correlation coefficient

Description

Density, distribution function, quantile function and random generator for the distribution of Fisher's transformation of Pearson's product moment correlation, based on a random sample from a bivariate normal distribution

Usage

dFPearson(x, N, rho = 0, log = FALSE)
pFPearson(q, N, rho = 0, lower.tail = TRUE, log.p = FALSE)
qFPearson(p, N, rho = 0, lower.tail = TRUE, log.p = FALSE)
rFPearson(n, N, rho = 0, lower.tail = TRUE, log.p = FALSE)

Arguments

x, q

Numeric vectors of quantiles.

N

Numeric vector. Number of observations, (N > 3).

rho

Numeric vector. Population correlations, (-1 < rho < 1).

log, log.p

A logical scalar; if TRUE, probabilities p are given as log(p).

lower.tail

A logical scalar. If TRUE (default), probabilities are P[X <= x], otherwise, P[X > x].

p

A numeric vector of probabilities in [0,1].

n

Numeric scalar. The number of observations to be simulated. If length(n) > 1 then length(n) is taken to be the number required.

References

Fisher, R. A. (1915). Frequency distribution of the values of the correlation coefficient in samples of an indefinitely large population. Biometrika, 10(4), 507-521. http://dx.doi.org/10.2307/2331838

Fisher, R. A. (1921). On the "probable error" of a coefficient of correlation deduced from a small sample. Metron, 1, 3-32. https://digital.library.adelaide.edu.au/dspace/bitstream/2440/15169/1/14.pdf

See Also

Pearson in the SuppDists package for dpqr functions for the untransformed Pearson produce moment correlation coefficient.

correlation: correlation sampling distribution movie.

Examples

# NOT RUN {
dFPearson(-1:1, N = 10)
dFPearson(0, N = 11:20)

pFPearson(0.5, N = 10)
pFPearson(0.5, N = 10, rho = c(0, 0.3))

qFPearson((1:9)/10, N = 10, rho = 0.2)
qFPearson(0.5, N = c(10, 20), rho = c(0, 0.3))

rFPearson(6, N = 10, rho = 0.6)
# }