Bisa | R Documentation |
Density, distribution function, and random generation for the Birnbaum-Saunders distribution.
dbisa(x, scale = 1, shape, log = FALSE)
pbisa(q, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
qbisa(p, scale = 1, shape, lower.tail = TRUE, log.p = FALSE)
rbisa(n, scale = 1, shape)
x , q |
vector of quantiles. |
p |
vector of probabilities. |
n |
Same as in |
scale , shape |
the (positive) scale and shape parameters. |
log |
Logical.
If |
lower.tail , log.p |
Same meaning as in |
The Birnbaum-Saunders distribution
is a distribution which is used in survival analysis.
See bisa
, the VGAM family function
for estimating the parameters,
for more details.
dbisa
gives the density,
pbisa
gives the distribution function, and
qbisa
gives the quantile function, and
rbisa
generates random deviates.
T. W. Yee and Kai Huang
bisa
.
## Not run:
x <- seq(0, 6, len = 400)
plot(x, dbisa(x, shape = 1), type = "l", col = "blue",
ylab = "Density", lwd = 2, ylim = c(0,1.3), lty = 3,
main = "X ~ Birnbaum-Saunders(shape, scale = 1)")
lines(x, dbisa(x, shape = 2), col = "orange", lty = 2, lwd = 2)
lines(x, dbisa(x, shape = 0.5), col = "green", lty = 1, lwd = 2)
legend(x = 3, y = 0.9, legend = paste("shape = ",c(0.5, 1,2)),
col = c("green","blue","orange"), lty = 1:3, lwd = 2)
shape <- 1; x <- seq(0.0, 4, len = 401)
plot(x, dbisa(x, shape = shape), type = "l", col = "blue",
main = "Blue is density, orange is the CDF", las = 1,
sub = "Red lines are the 10,20,...,90 percentiles",
ylab = "", ylim = 0:1)
abline(h = 0, col = "blue", lty = 2)
lines(x, pbisa(x, shape = shape), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qbisa(probs, shape = shape)
lines(Q, dbisa(Q, shape = shape), col = "red", lty = 3, type = "h")
pbisa(Q, shape = shape) - probs # Should be all zero
abline(h = probs, col = "red", lty = 3)
lines(Q, pbisa(Q, shape = shape), col = "red", lty = 3, type = "h")
## End(Not run)
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