Package 'jenga'

covid_in_europe data set

Description

A data frame with with daily and cumulative cases of Covid infections and deaths in Europe since March 2021.

Usage

covid_in_europe

Format

A data frame with 5 columns and 163 rows.

Source

www.ecdc.europa.eu

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jenga: automatic projections of time features using KNN

Description

Automatic projections of time features using KNN

Usage

jenga(
  df,
  seq_len = NULL,
  smoother = FALSE,
  k = NULL,
  method = NULL,
  kernel = NULL,
  ci = 0.8,
  n_windows = 10,
  mode = NULL,
  n_sample = 30,
  search = "random",
  dates = NULL,
  error_scale = "naive",
  error_benchmark = "naive",
  seed = 42
)

Arguments

df	A data frame with time features on columns (numerical or categorical features, but not both).
seq_len	Positive integer. Time-step number of the projected sequence
smoother	Logical. Perform optimal smoothing using standard loess (only for numerical features). Default: FALSE
k	Positive integer. Number of neighbors to consider when applying kernel average. Min number is 3. Default: NULL (automatic selection).
method	Positive integer. Distance method for calculating neighbors. Possibile options are: "euclidean", "manhattan", "minkowski". Default: NULL (automatic selection).
kernel	String. Distribution used to calculate kernel densities. Possible options are: "norm", "cauchy", "unif", "t". Default: NULL (automatic selection).
ci	Confidence interval. Default: 0.8
n_windows	Positive integer. Number of validation tests to measure/sample error. Default: 10.
mode	String. Sequencing method: deterministic ("segmented"), or non-deterministic ("sampled"). Default: NULL (automatic selection).
n_sample	Positive integer. Number of samples for grid or random search. Default: 30.
search	String. Two option available: "grid", "random". Default: "random".
dates	Date. Vector with dates for time features.
error_scale	String. Scale for the scaled error metrics. Two options: "naive" (average of naive one-step absolute error for the historical series) or "deviation" (standard error of the historical series). Default: "naive".
error_benchmark	String. Benchmark for the relative error metrics. Two options: "naive" (sequential extension of last value) or "average" (mean value of true sequence). Default: "naive".
seed	Positive integer. Random seed. Default: 42.

Value

This function returns a list including:

• exploration: list of all models, complete with predictions, test metrics, prediction stats and plot

• history: a table with the sampled models, hyper-parameters, validation errors

• best_model: results for the best model, including:

  • predictions: min, max, q25, q50, q75, quantiles at selected ci, and different statics for numerical and categorical variables

  • testing_errors: training and testing errors for one-step and sequence for each ts feature (different measures for numerical and categorical variables)

• time_log

Author(s)

Giancarlo Vercellino [email protected]

See Also

Useful links:

• https://rpubs.com/giancarlo_vercellino/jenga

Examples

jenga(covid_in_europe[, c(2, 3)], n_sample = 1)
jenga(covid_in_europe[, c(4, 5)], n_sample = 1)

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