multiJI {EWSmethods}

Multivariate S-map Jacobian index function

Description

Calculate a stability metric from the multivariate s-map estimated Jacobian

Usage

multiJI(data, winsize = 50, theta_seq = NULL, scale = TRUE)

Arguments

data

Numeric matrix with time in first column and species abundances in other columns

winsize

Numeric. Defines the window size of the rolling window as a percentage of the time series length.

theta_seq

Numeric vector of thetas (nonlinear tuning parameters) to estimate the Jacobian over. If 'NULL', a default sequence covering '0:8' is provided.

scale

Boolean. Should data be scaled within each window prior to estimating the Jacobian.

Value

A dataframe where the first column is last time index of the window and the second column is the estimated index value. A value <1.0 indicates stability, a value >1.0 indicates instability.

Source

Ushio, M., Hsieh, Ch., Masuda, R. et al. (2018) Fluctuating interaction network and time-varying stability of a natural fish community. Nature 554, 360–363.

Examples

#Load the multivariate simulated
#dataset `simTransComms`

data(simTransComms)

#Subset the third community prior to the transition

pre_simTransComms <- subset(simTransComms$community3,time < inflection_pt)

#Estimate the stability index for the third community
#(trimmed for speed)

egJI <- multiJI(data = pre_simTransComms[1:10,2:5],
winsize = 75)