pexp | R Documentation |
Density, distribution function, quantile function and random generation for a generalisation of the exponential distribution, in which the rate changes at a series of times.
dpexp(x, rate = 1, t = 0, log = FALSE)
ppexp(q, rate = 1, t = 0, lower.tail = TRUE, log.p = FALSE)
qpexp(p, rate = 1, t = 0, lower.tail = TRUE, log.p = FALSE)
rpexp(n = 1, rate = 1, t = 0, start = min(t))
x , q |
vector of quantiles. |
rate |
vector of rates. |
t |
vector of the same length as |
log , log.p |
logical; if TRUE, probabilities p are given as log(p), or log density is returned. |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
p |
vector of probabilities. |
n |
number of observations. If |
start |
numeric scalar; delayed entry time. The random deviates will be left truncated from this start time. |
Consider the exponential distribution with rates r_1, \ldots,
r_n
changing at times t_1, \ldots,
t_n
, with t_1 = 0
. Suppose t_k
is
the maximum t_i
such that t_i < x
. The density of
this distribution at x > 0
is f(x)
for k = 1
, and
\prod_{i=1}^k (1 - F(t_{i} - t_{i-1}, r_i)) f(x - t_{k},
r_{k})
for k > 1.
where F()
and f()
are the distribution and density functions of
the standard exponential distribution.
If rate
is of length 1, this is just the standard exponential
distribution. Therefore, for example, dpexp(x)
, with no other
arguments, is simply equivalent to dexp(x)
.
Only rpexp
is used in the msm
package, to simulate from Markov
processes with piecewise-constant intensities depending on time-dependent
covariates. These functions are merely provided for completion, and are not
optimized for numerical stability or speed.
dpexp
gives the density, ppexp
gives the distribution
function, qpexp
gives the quantile function, and rpexp
generates random deviates.
C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk
dexp
, sim.msm
.
x <- seq(0.1, 50, by=0.1)
rate <- c(0.1, 0.2, 0.05, 0.3)
t <- c(0, 10, 20, 30)
## standard exponential distribution
plot(x, dexp(x, 0.1), type="l")
## distribution with piecewise constant rate
lines(x, dpexp(x, rate, t), type="l", lty=2)
## standard exponential distribution
plot(x, pexp(x, 0.1), type="l")
## distribution with piecewise constant rate
lines(x, ppexp(x, rate, t), type="l", lty=2)
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