extended_lnlp | R Documentation |

`extended_lnlp`

performs the regularized S-map introduced in Censi et al. (2019) Methods in Ecology and Evolution. Multivariate S-map is also supported.

```
extended_lnlp(
block_time,
lib = c(1, NROW(block_time)),
pred = lib,
tp = 1,
target_column = 1,
lib_column = 1:NCOL(block_time),
num_neighbors = NCOL(block_time) + 1,
theta = 0,
dist_w = NULL,
regularized = FALSE,
lambda = NULL,
alpha = 0,
glmnet_parallel = FALSE,
random_seed = NULL,
save_smap_coefficients = FALSE
)
```

`block_time` |
Dataframe or matrix. Original time series. |

`lib` |
Numeric vector. Library indices. |

`pred` |
Numeric vector. Prediction indices. |

`tp` |
Forecasting time ahead. |

`target_column` |
Numeric. Indicates target column |

`lib_column` |
Numeric. Indicates library column |

`num_neighbors` |
Numeric. The number of nearest neighbors. |

`theta` |
Numeric. Weighing function for S-map. |

`dist_w` |
Matrix. Distance matrix used to calculate weights for S-map. Implemented for MDR S-map (Chang et al. 2021) Ecology Letters. If |

`regularized` |
Logical If |

`lambda` |
Numeric. Specify the strength of penalty in the regularization. |

`alpha` |
Numeric. |

`glmnet_parallel` |
Logical. If TRUE, the computation will be parallel (currently, experimental). |

`random_seed` |
Numeric. Random seed. |

`save_smap_coefficients` |
Logical. If |

Cenci, S, Sugihara, G, Saavedra, S. Regularized S-map for inference and forecasting with noisy ecological time series. Methods Ecol Evol. 2019; 10: 650– 660. https://doi.org/10.1111/2041-210X.13150

A list containing:

`model_output` | Model predictions |

`stats` | Statistics. |

`smap_coefficients` | S-map coefficients |

```
# extended_lnlp()
```

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