Description Usage Arguments Details Value Note Author(s) Examples
Generates predicted values, standard errors and confidence intervals for glmmADMB fits
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object |
A fitted model from |
newdata |
An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used. |
type |
Whether to return predictions on the
scale of the linear predictor ( |
se.fit |
A switch indicating if standard errors are required. |
interval |
What type of confidence intervals to return |
random |
Specification of random effects to use (STUB) |
level |
Tolerance/confidence level |
... |
further arguments passed to or from other methods. |
Produces predicted values from the model, based on evaluating the model with 'newdata' (if specified). If the logical 'se.fit' is 'TRUE', standard errors are calculated (this is only available on the link scale). It
predict.lm
produces a vector of predictions or a data frame of
predictions and bounds with column names fit
, lwr
, and
upr
if interval
is set. If se.fit
is
TRUE
, a list with the components fit
(vector or matrix as above) and se.fit
(standard error of predicted means) is returned.
Prediction is currently available only at the population level (i.e. with all random effects terms set to zero).
Confidence intervals and standard errors neglect uncertainty due to random effects, as well as the uncertainty of random effects. For more accurate confidence intervals, use MCMC-sampling methods.
Ben Bolker (partially copied from predict.lm
)
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