This should be in the online help but I agree it is hard to find so will check with our Documentation lead where this is;

<the blue line is a LOESS regression of all values, whereas the top redline is a LOESS of all residuals after being made positive, and the lower red line its' mirror.>

e.g.

https://onlinehelp.c...832_Plot_output**IWRES vs IVAR (Individual; Simple): **Plot of individual weighted residuals (IWRES) versus the independent variable (IVAR, e.g., time). Ideally, the blue line should be at 0 and the red line (with its negative reflection) should not show any fanning. Fanning indicates room for improving the distribution of residuals.

The stdev0 is the residual error of the observations i.e. CEps. so depends on your residual error model type, ie. additive you can think of this as an absolute value relative to the observations as you are assuming a uniform error;

error(CEps = 0.20532149859721)

observe(CObs = C + CEps)

whereas multiplicative assumes an error proportional to conc so CEps of 0.1 is suggesting 10%

error(CEps = 0.1)

observe(CObs = C * (1 + CEps))

Simon

PS 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. The span parameter in R gives the proportion of points in the plot which influence the smooth at each value. A scientific consultant got the same results for the plot using the R default span parameter = 2/3: As you can see from the plot, the data points are not distributed evenly, especially those sparse data at the beginning that the default Loess parameter value is not able to capture. Changing the smooth span parameter in R to = 0.08 gives a better result: There is no option to change the alpha parameter in Phoenix ? this is determined automatically based on the number of points. One suggestion would be to instead use linear regression to replot IPRED vs DV from the Residuals output worksheet.

**Edited by Simon Davis, 08 June 2022 - 08:43 AM.**