exponential {VGAM} | R Documentation |
Maximum likelihood estimation for the exponential distribution.
exponential(link = "loge", earg = list(), location = 0, expected = TRUE)
link |
Parameter link function applied to the positive parameter rate.
See Links for more choices.
|
earg |
List. Extra argument for the link.
See earg in Links for general information.
|
location |
Numeric of length 1, the known location parameter, A, say.
|
expected |
Logical. If TRUE Fisher scoring is used,
otherwise Newton-Raphson. The latter is usually faster.
|
The family function assumes the response Y has density
f(y) = rate * exp(-rate * (y-A))
for y > A, where A is the known location parameter. By default, A=0. Then E(Y) = A + 1/rate and Var(Y) = 1/rate^2.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.
Suppose A=0.
For a fixed time interval, the number of events is
Poisson with mean rate if the time
between events has a
geometric distribution with mean 1/rate.
The argument rate
in exponential
is the same as
rexp
etc.
The argument lambda
in rpois
is somewhat
the same as rate
here.
T. W. Yee
Evans, M., Hastings, N. and Peacock, B. (2000) Statistical Distributions, New York: Wiley-Interscience, Third edition.
amlexponential
,
laplace
,
poissonff
,
mix2exp
,
freund61
.
nn = 100 x1 = runif(nn) - 0.5 x2 = runif(nn) - 0.5 eta = 0.2 - 0.7 * x1 + 1.9 * x2 rate = exp(eta) y = rexp(nn, rate=rate) stem(y) fit = vglm(y ~ x1 + x2, exponential, trace=TRUE, crit="c") # slower fit = vglm(y ~ x1 + x2, exponential(exp=FALSE), trace=TRUE, crit="c") # faster coef(fit) coef(fit, mat=TRUE) Coef(fit) summary(fit)