ESM_SIM_DATA_ANN_UNPRUNNED
Description:
ESM_sim_data_3. Estimates of contribution of MCSim parameters to variation in biodiversity metrics based on contribution statistics from artificial neural networks (ANNs) trained and validated on simulated metacommunity outcomes.
File:
Variables (click to expand):
Diversity Metric ID
- Label:
- Definition: Diversity Metric ID
- Type: Nominal
- Missing values: None specified
Predictor Variable
- Label:
- Definition: Predictor Variable
- Type: Nominal
- Missing values: None specified
Predictor contribution to variation in response variable
- Label:
- Definition: Predictor contribution to variation in response variable
- Type: Nominal
- Missing values: None specified
Contribution p value
- Label:
- Definition: Contribution p value
- Type: Nominal
- Missing values: None specified
Predictor relative importance (RI) to variatino in response variable
- Label:
- Definition: Predictor relative importance (RI) to variatino in response variable
- Type: Nominal
- Missing values: None specified
RI p value
- Label:
- Definition: RI p value
- Type: Nominal
- Missing values: None specified
Keep predictor in pruned model?
- Label:
- Definition: Keep predictor in pruned model?
- Type: Nominal
- Missing values: None specified
N permutations used to estimate p values
- Label:
- Definition: N permutations used to estimate p values
- Type: Nominal
- Missing values: None specified