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gompertz(lshape = "loge", lscale = "loge",
ishape = NULL, iscale = NULL,
nsimEIM = 500, zero = NULL)
a
,
scale parameter scale
.
All parameters are positive.
See Links
for more choices.NULL
means a value is computed internally."vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.makeham
apply here too.scale
,
and $\alpha$ is called the shape parameter
(one could refer to $\alpha$ as a location parameter and $\beta$ as
a shape parameter---see Lenart (2012)).
The mean is involves an exponential integral function.
Simulated Fisher scoring is used and multiple responses are handled.The Makeham distibution has an additional parameter compared to the Gompertz distribution. If $X$ is defined to be the result of sampling from a Gumbel distribution until a negative value $Z$ is produced, then $X = -Z$ has a Gompertz distribution.
dgompertz
,
makeham
.gdata <- data.frame(x2 = runif(nn <- 1000))
gdata <- transform(gdata, eta1 = -1,
eta2 = -1 + 0.2 * x2,
ceta1 = 1,
ceta2 = -1 + 0.2 * x2)
gdata <- transform(gdata, shape1 = exp(eta1),
shape2 = exp(eta2),
scale1 = exp(ceta1),
scale2 = exp(ceta2))
gdata <- transform(gdata, y1 = rgompertz(nn, shape = shape1, scale = scale1),
y2 = rgompertz(nn, shape = shape2, scale = scale2))
fit1 <- vglm(y1 ~ 1, gompertz, data = gdata, trace = TRUE)
fit2 <- vglm(y2 ~ x2, gompertz, data = gdata, trace = TRUE)
coef(fit1, matrix = TRUE)
Coef(fit1)
summary(fit1)
coef(fit2, matrix = TRUE)
summary(fit2)
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