enzyme | R Documentation |
enzyme : The data comprise independent measurement of enzyme activity in the blood of 245 individuals. The data were analysed by Bechker at al. (1993).
brains : the brain size, brain
, and body weight, body
,
for 28 differnt animals.
data(enzyme)
data(brains)
enzyme : data frame with 245 observations on the following variable act
.
brains : data frame with 28 observations on the following variables. body
, brain
act
a numeric vector showing enzyme activity in the blood of 245 individuals.
body
a numeric vector showing the body weight of 28 differnt animals
brain
a numeric vector showing the brain size of 28 differnt animals
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.
Stasinopoulos M.D., Kneib T, Klein N, Mayr A, Heller GZ. (2024) Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications. Cambridge University Press.
(see also https://www.gamlss.com/).
data(enzyme)
hist(enzyme$act)
data(brains)
brains$lbrain<-log(brains$brain)
brains$lbody<-log(brains$body)
with(brains, plot(lbrain~lbody))
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