We are proud to announce the first release of the new xpose v0.4.0 package on CRAN thanks to a joint effort between Pharmetheus, Pfizer and Uppsala University.
Inspired by xpose4, this new version is actively being redesigned around the popular tidyverse packages ggplot2, dplyr and readr. This enables the creation of simple workflows for model diagnostics:
xpose_data(runno = '001') %>% # Import model output
filter(OCC == 3) %>% # Use dplyr verbs to modify the xpdb
dv_vs_ipred(aes(point_color = SEX, line_color = SEX), # Easily map variable to sub layers
title = 'Hello ISOP! The OFV is @ofv', # Add keywords to the plot labels they will be replaced by their actual value
facets = 'MED1',
ncol = 1, nrow = 1, page = 1:2) %>% # Facet over multiple pages in ggplot2
xpose_save(file = 'dv_vs_ipred.pdf') # Just save your the plots
We have added plenty of other features to help modelers though their daily work. To get started, don’t miss our live ISOP webinar on December 8th. You can also take a look at the xpose website and our xpose cheat-sheet:
Sincerely,
The xpose development team
B. Guiastrennec, A.C. Hooker, A. Olofsson, S. Ueckert,
R. Keizer, K. Harling, M.K. Smith, E. Plan and M.O. Karlsson