Betanorm | R Documentation |
Density, distribution function, quantile function and random generation for the univariate beta-normal distribution.
dbetanorm(x, shape1, shape2, mean = 0, sd = 1, log = FALSE) pbetanorm(q, shape1, shape2, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE) qbetanorm(p, shape1, shape2, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE) rbetanorm(n, shape1, shape2, mean = 0, sd = 1)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations.
Same as |
shape1, shape2 |
the two (positive) shape parameters of the standard beta
distribution. They are called |
mean, sd |
the mean and standard deviation of the univariate
normal distribution
( |
log, log.p |
Logical.
If |
lower.tail |
Logical. If |
The function betauninormal
, the VGAM family function
for estimating the parameters,
has not yet been written.
dbetanorm
gives the density,
pbetanorm
gives the distribution function,
qbetanorm
gives the quantile function, and
rbetanorm
generates random deviates.
T. W. Yee
Gupta, A. K. and Nadarajah, S. (2004). Handbook of Beta Distribution and Its Applications, pp.146–152. New York: Marcel Dekker.
## Not run: shape1 <- 0.1; shape2 <- 4; m <- 1 x <- seq(-10, 2, len = 501) plot(x, dbetanorm(x, shape1, shape2, m = m), type = "l", ylim = 0:1, las = 1, ylab = paste0("betanorm(",shape1,", ",shape2,", m=",m, ", sd=1)"), main = "Blue is density, orange is the CDF", sub = "Gray lines are the 10,20,...,90 percentiles", col = "blue") lines(x, pbetanorm(x, shape1, shape2, m = m), col = "orange") abline(h = 0, col = "black") probs <- seq(0.1, 0.9, by = 0.1) Q <- qbetanorm(probs, shape1, shape2, m = m) lines(Q, dbetanorm(Q, shape1, shape2, m = m), col = "gray50", lty = 2, type = "h") lines(Q, pbetanorm(Q, shape1, shape2, m = m), col = "gray50", lty = 2, type = "h") abline(h = probs, col = "gray50", lty = 2) pbetanorm(Q, shape1, shape2, m = m) - probs # Should be all 0 ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.