sumoR.RdCompile summary information similar to that of the sumo PSN function, based on the NONMEM output files lst, ext, and if covariance setp was run, the cov file.
sumoR(
model,
use.model.path = TRUE,
tableType = 2,
format.estimate = "% -#6.4g",
format.rse = "%#6.3g"
)name of the lst file with or without the .lst extension. model may include full or relative path to the lst file.
Load file from a global defined model library (TRUE=default).
If so will look for a global character vector named model.path
Table type for THETA's, OMEGA's and SIGMA's
tableType=0: Present OMEGA and SIGMA as variance and covariances and display SE for THETA, OMEGA, SIGMA
tableType=1: Present OMEGA and SIGMA as variance and covariances and display RSE for THETA, OMEGA, SIGMA
tableType=2: Present OMEGA and SIGMA as standard-deviation and correlations and display RSE for THETA, OMEGA, SIGMA
tableType=3: Present OMEGA and SIGMA as standard-deviation and correlations and display SE for THETA, OMEGA, SIGMA
format for estimated value, passed to sprintf
format for RSE or SE, passed to sprintf
named list of class sumoR
##### Compile summary information from the .lst file "run001.lst"
# 1) Get path to the example file included in nonmem2R package
file1 <- system.file("extdata", "run001.lst", package = "nonmem2R")
# 2) Compile summary information from "run001.lst"
sumoR(file1)
#>
#> NONMEM output summary: /tmp/RtmpxZMFyo/temp_libpath6fa751979b754/nonmem2R/extdata/run001
#>
#> Successful minimization [ OK ]
#> No rounding errors [ OK ]
#> No final zero gradients [ OK ]
#> Hessian not reset [ OK ]
#> Successful covariance step [ OK ]
#>
#> Number of observation records 837
#> Number of individuals 33
#>
#> Objective function value 6130.99
#> Number significant digits in estimates 3.40
#> Condition number 166.17
#>
#> ETA shrinkage(%) 0.0 26.9 3.9 100.0 0.2 100.0 2.0
#> EPS shrinkage(%) 8.5
#>
#>
#> Theta Omega Sigma
#> 1 27.73 (0.0652) [1,1] 0.2654 ( 0.220)
#> 2 112.8 (0.0945) [2,2] 0.1967 ( 0.179)
#> 3 98.25 (0.0651) [3,3] 0.2074 ( 0.135)
#> 4 20.81 ( 0.115) [5,5] 0.3832 ( 0.115)
#> 5 0.1682 (0.0516) [7,7] 0.2251 ( 0.183)
#> 6 0.9382 (0.0760)
#> 8 15.60 (0.0372)
#> 9 9.696 (0.0422)
#> 10 44.52 (0.0505)
#> 11 5.560 (0.0700)
#> 12 0.1455 (0.0511)
#> 13 1.657 (0.0990)
#> 14 1.077 ( 0.149)
#> 15 1.958 (0.0964)