
Maximum likelihood estimation of the (univariate) lognormal distribution.
lognormal(lmeanlog = "identitylink", lsdlog = "loge", zero = "sdlog")
Parameter link functions applied to the mean and (positive)
Links
for more choices.
Specifies which
linear/additive predictor is modelled as intercept-only.
For lognormal()
,
the values can be from the set {1,2} which correspond to
mu
, sigma
, respectively.
See CommonVGAMffArguments
for more information.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.
A random variable
Kleiber, C. and Kotz, S. (2003) Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ, USA: Wiley-Interscience.
Lognormal
,
uninormal
,
CommonVGAMffArguments
,
simulate.vlm
.
# NOT RUN {
ldata2 <- data.frame(x2 = runif(nn <- 1000))
ldata2 <- transform(ldata2, y1 = rlnorm(nn, mean = 1 + 2 * x2, sd = exp(-1)),
y2 = rlnorm(nn, mean = 1, sd = exp(-1 + x2)))
fit1 <- vglm(y1 ~ x2, lognormal(zero = 2), data = ldata2, trace = TRUE)
fit2 <- vglm(y2 ~ x2, lognormal(zero = 1), data = ldata2, trace = TRUE)
coef(fit1, matrix = TRUE)
coef(fit2, matrix = TRUE)
# }
Run the code above in your browser using DataLab