Calculating Optimum Sampling Effort in Community Ecology
Power curves for different sampling efforts
ecocbo: Calculating Optimum Sampling Effort in Community Ecology
Plot Statistical Power and Pseudo-F Distributions
Power curves for different sampling efforts
Prepare Data for Evaluation
S3Methods for Printing
S3Methods for Printing
Simulated Components of Variation
Calculate Beta Error and Statistical Power from Simulated Samples
Cost-Benefit Optimization for Sampling Effort
Power surface for different sampling efforts
Cost-Benefit Optimization after Underwood's equations
A system for calculating the optimal sampling effort, based on the ideas of "Ecological cost-benefit optimization" as developed by A. Underwood (1997, ISBN 0 521 55696 1). Data is obtained from simulated ecological communities with prep_data() which formats and arranges the initial data, and then the optimization follows the following procedure of four functions: (1) prep_data() takes the original dataset and creates simulated sets that can be used as a basis for estimating statistical power and type II error. (2) sim_beta() is used to estimate the statistical power for the different sampling efforts specified by the user. (3) sim_cbo() calculates then the optimal sampling effort, based on the statistical power and the sampling costs. Additionally, (4) scompvar() calculates the variation components necessary for (5) Underwood_cbo() to calculate the optimal combination of number of sites and samples depending on either an economic budget or on a desired statistical accuracy. Lastly, (6) plot_power() helps the user visualize the results of sim_beta().