Extracts the within-period aggregation weights applied to each indicator.
For parametric aggregators ("expalmon", "beta") these are the weights
implied by the estimated parameters; for user-supplied numeric aggregators
they are the supplied weights.
Usage
# S3 method for class 'mf_model'
weights(object, indicator = NULL, ...)Arguments
- object
A fitted
"mf_model"object returned bymf_model().- indicator
Optional indicator selector, either an indicator name or a position. When supplied, the weights for that single indicator are returned directly; when
NULL(default), a named list covering every indicator is returned.- ...
Unused.
Value
When indicator is NULL, a named list with one element per
indicator, each either a numeric weight vector or NULL for indicators
whose aggregator does not imply a fixed weight vector ("unrestricted").
When indicator is supplied, that single element.
Details
The deterministic rules imply the fixed weight vectors of
\(\tilde x_t = \sum_m w_m x_{t,m}\): "mean" gives \(w_m = 1/M\),
"last" gives \(w_M = 1\) and zero elsewhere, and "sum" gives
\(w_m = 1\). These are returned alongside the estimated and
user-supplied weights, so the accessor reports the weights actually
applied whichever aggregator was chosen. "unrestricted" has no single
weight vector, because it estimates one coefficient per within-period
observation instead of aggregating; it returns NULL, as does an
indicator aligned with indic_predict = "direct".
See also
aggregation_parameters() for the underlying parametric
parameters, and indicators() for the available indicator names.
Examples
gdp_growth <- tsbox::ts_pc(gdp)
#> [value]: 'values'
#> [value]: 'values'
gdp_growth <- tsbox::ts_na_omit(gdp_growth)
#> [value]: 'values'
model <- mf_model(
target = gdp_growth,
indic = baro,
indic_aggregators = "expalmon",
h = 1
)
weights(model)
#> $baro
#> [1] 6.142366e-03 9.938573e-01 3.314536e-07
#>
weights(model, indicator = 1)
#> [1] 6.142366e-03 9.938573e-01 3.314536e-07