How did the IWRES be calculated from the output data? Is the IWRES=(DV-predicted)/weight ?
what is detailcalculationinformation of LOESS regressionincluding (1) degree of local polynomials, (2) smoothing parameter, and (3) weight function in the IWRES vs IPRED (orI****WRES vs IVAR)?
the Phoenix Loess function uses the Cleveland-Grosse Bell labs fortran 77 implementation in Netlib. See http://www.netlib.org/a/loess for a description. The smoothing parameter, alpha, is determined automatically and depends on the number of points: if(n.gt.10) alpha=1 if(n.gt.10) alpha=.9 if(n.gt.15) alpha=.8 if(n.gt.20) alpha=.7 if(n.gt.50) alpha=.6 if(n.ge.100) alpha=.5 if(n.ge.200) alpha=.5 if(n.ge.500) alpha=.5 if(n.ge.1000) alpha=0.5 In most of the case, the default smoothing value is good enough.
Thanks for all of your reply. Based on the article and link, I also have some questions:
IWRES- I would like to confirm If the weight for an additive error model under individual mode is the square root of the variance of the residual error? cause we are NOT using population PK model but individual mode.
The weight of LOESS created from Phoenix is described in the code written in Fortran. However, I am not able to get understand with it. Could anyone help me to transfer into a layman’s term how the weight is calculated ?
For the weight function in LOESS, it is to give individual observations in the sum of squared residuals a different weight in the local fitting criterion.