The xpose plots • xpose

Basic goodness-of-fit plots

Plots of the independent variable (IDV)

dv_vs_idv(xpdb_ex_pk)

ipred_vs_idv(xpdb_ex_pk)

pred_vs_idv(xpdb_ex_pk)

dv_preds_vs_idv(xpdb_ex_pk)

DV vs. PREDs plots

dv_vs_pred(xpdb_ex_pk)

dv_vs_ipred(xpdb_ex_pk)

Residual plots

res_vs_idv(xpdb_ex_pk, res = 'CWRES')

res_vs_pred(xpdb_ex_pk, res = 'CWRES')

absval_res_vs_idv(xpdb_ex_pk, res = 'CWRES')

absval_res_vs_pred(xpdb_ex_pk, res = 'CWRES')

Minimization plots

prm_vs_iteration(xpdb_ex_pk, labeller = 'label_value')

grd_vs_iteration(xpdb_ex_pk, labeller = 'label_value')

Individual plots

ind_plots(xpdb_ex_pk, page = 1)

Distributions

Histograms and density plots

prm_distrib(xpdb_ex_pk)

eta_distrib(xpdb_ex_pk)

res_distrib(xpdb_ex_pk)

cov_distrib(xpdb_ex_pk)

QQ plots

prm_qq(xpdb_ex_pk)

eta_qq(xpdb_ex_pk)

res_qq(xpdb_ex_pk)

cov_qq(xpdb_ex_pk)

Kinetic plots

Compartment’s amount

amt_vs_idv(xpdb_ex_pk, nrow = 2, ncol = 1)

Visual predictive checks (VPC)

Continuous vpc

xpdb_ex_pk %>% 
 vpc_data(opt = vpc_opt(n_bins = 7)) %>% 
 vpc()

Censored vpc

xpdb_ex_pk %>% 
 vpc_data(vpc_type = 'censored', opt = vpc_opt(lloq = 1, n_bins = 7)) %>% 
 vpc()

Categorical vpc

xpdb_ex_pk %>% 
 vpc_data(vpc_type = 'categorical') %>% 
 vpc()