Description Usage Arguments Value Examples
The function takes in argument the observed weigted parameters of ED50 i.e mu_A and sigma_A, and the formula of the best models for prediction of mu_C_act and sigma_C_act and return the muC_act and SigmaC_act They are estimated using a cross validation. When parameters of one class are predicted data of that class are not taken in acount in the regression step
1 | predict_PC(PAC_obs, form_mu, form_sigma)
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PAC_obs |
dataframe containing the observed acute and chronic weighted parameters |
form_mu |
Formula of the best model selected to predict muC_act |
form_sigma |
Formula of the best model selected to predict SigmaC_act |
a list with the Chronic predicted parameters (MuC_act and SigmaC_act) , regression coefficients for MuC_reg and SigmaC_reg and sd of residuals for both regressions NB : means of residuals = 0 by definition
1 2 3 4 5 | library(ACTpckg)
data(cipr)
ciprKP <- subset_data(cipr, Class,6)
PAC_obs<-est_PAC(ciprKP,Class)
PC_pred <- predict_PC(PAC_obs,bm_mu, bm_sigma)
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