ranger_augmented_estimate: Estimate random forest (ranger) model using tsibble with...
In kassandra-ru/kassandr: Functions to Forecast Russian Macro Data in Kassandra Project
Description
Usage
Arguments
Details
Value
Examples
Description
Estimate random forest (ranger) using tsibble with regressors
Usage
1
ranger_augmented_estimate(augmented, target = "value", seed = 777)
Arguments
augmented
tsibble with all predictors with lags.
May be obtained using 'augment_tsibble_4_regression'.
target
name of the target variable
seed
random seed
Details
Estimate random forest (ranger) model using tsibble with regressors.
Regressors should already include lags, fourier terms, trend etc
Value
lasso model
Examples
1
2
3
4
test_ts = stats::ts(rnorm(100), start = c(2000, 1), freq = 12)
test_tsibble = tsibble::as_tsibble(test_ts)
augmented = augment_tsibble_4_regression(test_tsibble, h = 4)
model = ranger_augmented_estimate(augmented)
kassandra-ru/kassandr documentation built on Jan. 1, 2022, 7:39 a.m.
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Description Usage Arguments Details Value Examples
Description
Estimate random forest (ranger) using tsibble with regressors
Usage
1 | ranger_augmented_estimate(augmented, target = "value", seed = 777)
|
Arguments
augmented |
tsibble with all predictors with lags. May be obtained using 'augment_tsibble_4_regression'. |
target |
name of the target variable |
seed |
random seed |
Details
Estimate random forest (ranger) model using tsibble with regressors. Regressors should already include lags, fourier terms, trend etc
Value
lasso model
Examples
1 2 3 4 | test_ts = stats::ts(rnorm(100), start = c(2000, 1), freq = 12)
test_tsibble = tsibble::as_tsibble(test_ts)
augmented = augment_tsibble_4_regression(test_tsibble, h = 4)
model = ranger_augmented_estimate(augmented)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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