Value
-
-
-
Predicted values on the appropriate scale.
+
Predicted values on the appropriate scale.
If summary = FALSE
and type != "terms"
,
-the output is a matrix of dimension n_draw x n_observations
-
-
-
containing predicted values for each posterior draw in object
.
-
-
-
If summary = TRUE
and type != "terms"
, the output is an n_observations
x E
-
-
-
matrix. The number of summary statistics E
is equal to 2 +
+the output is a matrix of dimension n_draw x n_observations
+containing predicted values for each posterior draw in object
.
+
If summary = TRUE
and type != "terms"
, the output is an n_observations
x E
+matrix. The number of summary statistics E
is equal to 2 +
length(probs)
: The Estimate
column contains point estimates (either
mean or median depending on argument robust
), while the
Est.Error
column contains uncertainty estimates (either standard
deviation or median absolute deviation depending on argument
robust
). The remaining columns starting with Q
contain
quantile estimates as specified via argument probs
.
-
-
-
If type = "terms"
and summary = FALSE
, the output is a named list
-
-
-
containing a separate slot for each effect, with the effects returned as
+
If type = "terms"
and summary = FALSE
, the output is a named list
+containing a separate slot for each effect, with the effects returned as
matrices of dimension n_draw x 1
. If summary = TRUE
, the output resembles that
from predict.gam
when using the call
predict.gam(object, type = "terms", se.fit = TRUE)
, where mean contributions
from each effect are returned in matrix
form while standard errors (representing
the interval: (max(probs) - min(probs)) / 2
) are returned in a separate matrix
-
-