Set up the packages | datasets from Rcurvep package | When no preferred BMR and would like to do a exhaustive search | Calculate 10 times and compare the results | When preferred BMRs are available for endpoints | Get the BMRs for each endpoint | Join the BMRs to the concentration-response data | Set up the expressions | Fitting based on simulated curves using run_fit | Fitting based on simulated curves using run_fit and pmap | Fitting based on original data | Use modls = hill parameter | Calculate 5 times and compare the results | Use modls = cc2 parameter

Install the package | Load the library | Load the sample dataset | Rcurvep method | Run Rcurvep on datasets using combi_run_rcurvep() | Run Rcurvep when there is a preferred BMR | Summarize activity data from Rcurvep | Add confidence interval for activity data from Rcurvep | Run Rcurvep when an optimal/preferred BMR is unknown | Estimate the BMR | Display the diagnostic curves for BMR estimation | Run parametric fitting on datasets | Summarize parametric fitting results using a preferred BMR | Inspect concordance between two parametric fits | Add confidence interval for activity data from parametric fitting (currently is only available to 3-parameter Hill equation from tcpl)