params: ctr: "" title: ""



subtitle: r params$ctr$save_dir title: r params$title


library(ggplot2)
knitr::opts_chunk$set(echo = FALSE,message=FALSE)
cats <- ctr %>% get_cats

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Key model diagnostics

Parameter Table

ctr %>% param_table(return_table = FALSE)

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NPDE vs PRED

ctr %>% pmx_plot_npde_pred

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NPDE vs TIME

ctr %>% pmx_plot_npde_time

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IWRES vs IPRED

ctr %>% pmx_plot_iwres_ipred

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IWRES vs TIME

ctr %>% pmx_plot_iwres_time

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Distribution of random effects

ctr %>% pmx_plot_eta_box

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VPC

ctr %>%
pmx_plot_vpc(
  bin=pmx_vpc_bin(within_strat=TRUE, style="quantile")
)

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Supplementary diagnostics

Distribution of IWRES

QQ plot of IWRES

ctr %>% pmx_plot_iwres_qq

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Distribution of IWRES

ctr %>% pmx_plot_iwres_dens

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EBE-based diagnostics

Distribution and correlation of EBEs

ctr %>% pmx_plot_eta_matrix

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EBE vs discrete covariates

ctr %>% pmx_plot_eta_cats

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EBE vs continuous covariates

ctr %>%  pmx_plot_eta_conts

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Observations vs predictions

DV vs PRED

ctr %>% pmx_plot_dv_pred

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DV vs IPRED

ctr %>% pmx_plot_dv_ipred

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Residual plots

|IWRES| vs IPRED

ctr %>% pmx_plot_abs_iwres_ipred

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Individual plots (selection)

 ctr %>% pmx_plot_individual

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Stratified key diagnostics

NPDE vs TIME by categorical covariates

ctr %>% pmx_plot_cats("npde_time")

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IWRES vs TIME by categorical covariates

ctr %>% pmx_plot_cats("iwres_time")

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VPC by categorical covariates

ctr %>%
pmx_plot_cats(
  "pmx_vpc",
  bin=pmx_vpc_bin(within_strat=TRUE, style="quantile")
)


ggPMXdevelopment/ggPMX documentation built on Dec. 11, 2023, 5:24 a.m.