Comments (3)
The best way to do this is probably using a function like read_table_nm
from xpose and vpc to grab the NONMEM output data, and then assign it to ggPMX's data structure. Once that's in place, all diagnostics should be quite straightforward to implement. The data needed should be fundamentally similar
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@kestrel99 tha nk you. read_table_nm looks like a good start. where we can find data to test it ?
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Related Issues (20)
- Use `readr::read_table()`
- Change `select()` usage
- Use `reframe()` intesad of `summarize()` or recast as data.table syntax
- Use `purr::map() + purr::exec()`
- Unknown error when creating controller HOT 2
- Make a `pmx_effects()` controller with documentation about what everything means AND more intuitive parameter names
- Remove captioner
- Too much white space for figures HOT 1
- Remove captioner for now (doesn't match match our internal standards)
- `use.title` = `FALSE`
- censoring defaults HOT 1
- Switch on/off sci notation for tables
- Conditionally include `nlmixr2`
- CRAN update
- Parameter table for Monolix 2013R1
- Observations Ignored in Individual Plots HOT 2
- No all plots using ggPMX and a Monolix project HOT 2
- CRAN package requirement.
- Bare theophylline controller creation call fails
- directory fixes for CRAN
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