TwoParExponential {tolerance} | R Documentation |
Density, distribution function, quantile function, and random generation for the 2-parameter
exponential distribution with rate equal to rate
and shift equal to shift
.
d2exp(x, rate = 1, shift = 0, log = FALSE) p2exp(q, rate = 1, shift = 0, lower.tail = TRUE, log.p = FALSE) q2exp(p, rate = 1, shift = 0, lower.tail = TRUE, log.p = FALSE) r2exp(n, rate = 1, shift = 0)
x,q |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
The number of observations. If length>1 , then the length is taken to be the number required. |
rate |
Vector of rates. |
shift |
Vector of shifts. |
log,log.p |
Logical vectors. If TRUE , then probabilities are given as log(p) . |
lower.tail |
Logical vector. If TRUE , then probabilities are P[X<= x], else P[X>x]. |
If rate
or shift
are not specified, then they assume the default values of 1 and 0, respectively.
The 2-parameter exponential distribution has density
f(x) = exp(-(x-μ)/β)/β
where x>=μ, μ is the shift parameter, and β>0 is the scale parameter.
d2exp
gives the density, p2exp
gives the distribution function, q2exp
gives the quantile
function, and r2exp
generates random deviates.
runif
and .Random.seed
about random number generation.
## Randomly generated data from the 2-parameter exponential ## distribution. set.seed(100) x <- r2exp(n = 500, rate = 3, shift = -10) hist(x, main = "Randomly Generated Data", prob = TRUE) x.1 = sort(x) y <- d2exp(x = x.1, rate = 3, shift = -10) lines(x.1, y, col = 2, lwd = 2) plot(x.1, p2exp(q = x.1, rate = 3, shift = -10), type = "l", xlab = "x", ylab = "Cumulative Probabilities") q2exp(p = 0.20, rate = 3, shift = -10, lower.tail = FALSE) q2exp(p = 0.80, rate = 3, shift = -10)