fit_inla_model  R Documentation 
Used within predict_inla()
, this function fits the model to the data
frame, working whether the model is being fit across the entire data frame or
being fit to each group individually. Data is filtered prior to fitting,
model(s) are fit, and then fitted values are generated on the original.
fit_inla_model(
df,
formula,
control.predictor,
...,
formula_vars,
test_col,
group_col,
group_models,
obs_filter,
sort_col,
sort_descending,
pred_col,
pred_upper_col,
pred_lower_col,
filter_na,
ret,
error_correct,
error_correct_cols,
shift_trend
)
df 
Data frame of model data. 
formula 
A formula that will be supplied to the model, such as 
control.predictor 
Used to set 
... 
Additional arguments passed to 
formula_vars 
Variables included in the model formula, generated by

test_col 
Name of logical column specifying which response values to remove
for testing the model's predictive accuracy. If 
group_col 
Column name(s) of group(s) to use in 
group_models 
Logical, if 
obs_filter 
String value of the form " If `group_models = FALSE`, then `obs_filter` is only used to determine when predicted values replace observed values but **is not** used to restrict values from being used in model fitting. If `group_models = TRUE`, then a model is only fit for a group if they meet the `obs_filter` requirements. This provides speed benefits, particularly when running INLA time series using `predict_inla()`. 
sort_col 
Column name(s) to use to 
sort_descending 
Logical value on whether the sorted values from 
pred_col 
Column name to store predicted value. 
pred_upper_col 
Column name to store upper bound of confidence interval
generated by the 
pred_lower_col 
Column name to store lower bound of confidence interval
generated by the 
filter_na 
Character value specifying how, if at all, to filter 
ret 
Character vector specifying what values the function returns. Defaults to returning a data frame, but can return a vector of model error, the model itself or a list with all 3 as components. 
error_correct 
Logical value indicating whether or not whether mean error
should be used to adjust predicted values. If 
error_correct_cols 
Column names of data frame to group by when applying error correction to the predicted values. 
shift_trend 
Logical value specifying whether or not to shift predictions
so that the trend matches up to the last observation. If 
If fitting models individually to each group, mdl
will never be returned, as
as these are instead a large group of models. Otherwise, a list of mdl
and df
is returned and used within predict_inla()
.
List of mdl
(fitted model) and df
(data frame with fitted values
and confidence bounds generated from the model).
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