Description Usage Arguments Details Value Examples
Evaluates the _conditional_ distribution implied by a tramME model, given by a set of covariates and random effects on a selected scale.
1 2 3 4 5 6 7 8 9 
object 
A 
newdata 
an optional data frame of observations 
ranef 
Random effects (either in named list format or a numeric vector) or the word "zero". See Details. 
type 
The scale on which the predictions are evaluated:

... 
Additional arguments, passed to 
When newdata
contains values of the response variable, prediction is only
done for those values. In this case, if random effects vector (ranef
) is not
supplied by the user, the function predicts the random effects from the model
using newdata
.
When no response values are supplied in newdata
, the prediction is done
on a grid of values for each line of the dataset (see predict.mlt
for information on how to control the setup of this grid).
In this case, the user has to specify the vector of random effects to avoid ambiguities.
The linear predictor (type = "lp"
) equals to the shift terms plus the random
effects terms _without the baseline transfromation function_.
The linear predictor (type = "lp"
) and the conditional quantile function
(type = "quantile"
) are special in that they do not return results evaluated
on a grid, even when the response variable in newdata
is missing. The probabilities
for the evaluation of the quantile function can be supplied with the prob
argument
of predict.mlt
.
In the case of type = "quantile"
, when the some of the requested conditonal
quantiles fall outside of the support of the response distribution
(specified when the model was set up), the inversion of the CDF cannot be done exactly
and tramME
returns censored values.
When ranef
is equal to "zero", a vector of zeros with the right size is
used.
A numeric vector/matrix of the predicted values (depending on the inputs)
or a response
object, when the some of the requested conditonal quantiles
fall outside of the support of the response distribution specified when the model
was set up (only can occur with type = "quantile"
).
1 2 3 4 5 6 7  data("sleepstudy", package = "lme4")
fit < BoxCoxME(Reaction ~ Days + (Days  Subject), data = sleepstudy)
predict(fit, type = "trafo") ## evaluate on the transformation function scale
nd < sleepstudy
nd$Reaction < NULL
pr < predict(fit, newdata = nd, ranef = ranef(fit), type = "distribution",
K = 100)

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