dLiland {fixedTimeEvents} | R Documentation |
The distribution of distances between discrete events in fixed time/space (the Liland distribution)
Description
Density, distribution function, quantile function and random generation
for the Liland distribution with R
trials and r
successes.
Usage
dLiland(x, R, r, warn = FALSE)
pLiland(q, R, r, lower.tail = TRUE, warn = FALSE)
qLiland(p, R, r)
rLiland(n, R, r)
Arguments
x , q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. |
R |
number of trials. |
r |
number of successes. |
warn |
logical indicating if a warning should be issued if approximation is used. |
lower.tail |
logical indicating if the lower tail of the distribution should be summed. |
Details
The Liland distribution has probability mass
f(X=x;R,r) =
\frac{{R-x \choose r-1}}{{R \choose r}}
where x
is the distance between consecutive successes, R
is the number of trials and r
is the number of successes.
Value
dLiland
gives the probability mass, pLiland
gives the distribution
function, qLiland
gives the quantile function, and rLiland
generates
random Liland values.
Author(s)
Kristian Hovde Liland
References
Liland, KH & Snipen, L, FixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time, SoftwareX 5 (2016).
See Also
Liland
, Liland.test
, simLiland
Examples
dLiland(19, R = 1949, r = 162)
pLiland(19, R = 1949, r = 162)
qLiland(0.5, R = 1949, r = 162)
plot( pLiland(1:100, R = 1949, r = 162) )
## QQ-plot of Liland distribution and random Liland values
R <- 2000
r <- 120
n <- 1000
samp <- rLiland(n,R,r)
theo <- qLiland(ppoints(n),R,r)
qqplot(theo,samp,
xlab='F(x;2000,120)', ylab='Sample (1000)', axes=FALSE)
axis(1,at=c(0,40,80,120))
axis(2,at=c(0,40,80,120))
box()
qqline(samp, distribution = function(p)qLiland(p,R=2000,r=120), col='gray',lty=2)