Forecasting Tipping Points at the Community Level

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Documentation for package ‘EWSmethods’ version 1.3.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

CODrecovery	Three Recovering Cod Populations
conda_clean	Python Removal
default_weights_path	Path to Model Weights
deseason_ts	Deseason Seasonal Time Series
detrend_ts	Detrend Time Series
embed_ts	Construct an Embedded Timeseries
ewsnet_finetune	EWSNet Finetune
ewsnet_init	EWSNet Initialisation
ewsnet_predict	EWSNet Predict
ewsnet_reset	Reset EWSNet Model Weights
FI	Calculate Fisher Information
II	Information Imbalance
imbalance_gain	Information Gain
multiAR	Multivariate Jacobian Index Estimated From Multivariate Autocorrelation Matrix
multiEWS	Multivariate Early Warning Signal Assessment
multiJI	Multivariate S-map Jacobian index function
multi_smap_jacobian	Multivariate S-map Inferred Jacobian
mvi	Multivariate Variance Index function
perm_rollEWS	Significance Testing of Rolling Window Early Warning Signals
plot.EWSmethods	Plot an EWSmethods object
simTransComms	Three Simulated Transitioning Communities.
tuneII	Information Imbalance Across Alphas
uniAR	Univariate Jacobian Index Estimated From Univariate Autocorrelation Matrix
uniEWS	Univariate Early Warning Signal Assessment
uniJI	Univariate S-map Jacobian index function
uni_smap_jacobian	Univariate S-map Inferred Jacobian