s_map_mdr_all: A all-in-one wrapper function for MDR S-map
In ong8181/macam: A collection of miscellaneous R functions for ecology

s_map_mdr_all

R Documentation

A all-in-one wrapper function for MDR S-map

Description

s_map_mdr_all A all-in-one wrapper function for MDR S-map. Detect causality between variables, construct data.frame for multiview embedding, compute multiview distance, and perform MDR S-map. For fine-tuning, use the step-by-step functions such as compute_mvd() etc..

Usage

s_map_mdr_all(
  block,
  effect_var,
  lib = c(1, nrow(block)),
  pred = lib,
  tp = 1,
  E_range = 0:10,
  tp_range = -4:0,
  n_ssr = 100,
  k = 10,
  theta = 0,
  regularized = FALSE,
  lambda = 0,
  alpha = 0,
  glmnet_parallel = FALSE,
  save_smap_coefficients = TRUE,
  silent = FALSE,
  random_seed = 1234
)

Arguments

`block`	Data.frame contains time series data. The first column should be the target column.
`effect_var`	Character or Numeric. Column name or index of the effect variable.
`lib`	Numeric vector. Library indices.
`pred`	Numeric vector. Prediction indices.
`tp`	Numeric. Forecasting time ahead.
`E_range`	Numeric. Embedding dimensions that will be tested.
`tp_range`	Numeric. `tp` tested for UIC.
`n_ssr`	Numeric. The total number of embeddings examined.
`k`	Numeric. The number of embeddings used to calculate ensemble distance.
`theta`	Numeric. Weighing function for S-map.
`regularized`	Logical If `TRUE`, regularized S-map will be performed. If `FALSE`, the normal S-map will be performed. Please use `rEDM::s_map` function.
`lambda`	Numeric. Specify the strength of penalty in the regularization.
`alpha`	Numeric. `alpha = 0` is the ridge regression, `alpha = 1` is the lasso regression, and `⁠0 < alpha < 1⁠` is an elastic net.
`glmnet_parallel`	Logical. If TRUE, the computation will be parallel (currently, experimental).
`save_smap_coefficients`	Logical. If `TRUE`, S-map coefficients will be saved.
`silent`	Logical. if `TRUE`, progress message will not be shown.
`random_seed`	Numeric. Random seed.