make_ccm_data {multispatialCCM}

Makes fake data for other functions

Description

Builds a fake data set of two interacting processes, based on the model in the Sugihara et al. publication below, and based on a two-species discrete-time competition model. In the model, process A is causally affected by process B, but process B is not influenced by process A.

Usage

make_ccm_data(sp_sd=0.125, obs_sd=0.025,
Sstr=0.375, times=10, burnin=100,
number_of_chains=20, seednum=2718)

Arguments

sp_sd

Standard deviation used to add process noise. If you are simulating multiple plots, this adds normally distributed noise with mean=0 to the growth rates of each species in different plots.

obs_sd

Standard deviation used to add observation error. Observation error is added to process X as a lognormal variable (X*rlnorm), with mean=0 on the lognormal scale.

Sstr

Forcing strength defining the effect of process B on process A.

times

Number of sequential observations desired for the time series in each plot (i.e., length of each independent time series)?

burnin

Burnin time before starting the experiment. This can be used to remove correlation among plots that occurs because of starting conditions.

number_of_chains

Total number of time series (i.e., how many replicates will be assembled into a single long time series?)

seednum

Random seed used for simulation.

Value

Accm

Time series for process A. Gaps between time series are indicated by a "NA" entry.

Bccm

Time series for process B. Gaps between time series are indicated by a "NA" entry.

time_ccm

Time indices corresponding to process A and B.

Author(s)

Adam Clark

References

Sugihara, G., R. May, H. Ye, C. Hsieh, E. Deyle, M. Fogarty, and S. Munch. 2012. Detecting Causality in Complex Ecosystems. Science 338.

Adam T. Clark, H. Ye, Forest Isbell, Ethan R. Deyle, Jane Cowles, David Tilman, and George Sugihara. 2015. Spatial ’convergent cross mapping’ to detect causal relationships from short time-series. Ecology, 96(6):1174–1181.

See Also

CCM_boot, SSR_pred_boot, SSR_check_signal, ccmtest

Examples

#Simulate data to use for multispatial CCM test
#See function for details - A is causally forced by B,
#but the reverse is not true.
ccm_data_out<-make_ccm_data()
Accm<-ccm_data_out$Accm
Bccm<-ccm_data_out$Bccm