Hello,

I’m unsuccessfully trying to apply piecewise linear regression over each of 22 groups.  The data structure of the reproducible toy dataset is below.  I’m using the ‘segmented’ package, it worked fine with a data set that containing only one group (“Lot.Run”).

$ Cycle   : int  1 2 3 4 5 6 7 8 9 10 ...
 $ Lot.Run : Factor w/ 22 levels "J062431-1","J062431-2",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ deltaWgt: num  38.7 42.6 41 42.3 40.6 ...

I am new to ‘segmented’, and also new to ‘plyr’, which is how I’m trying to apply this segmented regression to the 22 Lot.Run groups.  Within a Lot.Run, the piecewise linear regressions are deltaWgt vs. Cycle.

#####  define the linear regression #####
out.lm<-lm(deltaWgt~Cycle, data=Test50.df)

#####  define the function called by dlply  #####
       #####  find cutpoints via bootstrapping, fit the piecewise regressions  #####
segmentf_df <- function(df) {
 segmented(out.lm,seg.Z=~Cycle, psi=(Cycle=NA),control=seg.control(stop.if.error=FALSE,n.boot=0)), data = df)
 }

at this point, there’s an  error message
23] ERROR: <text>

#####  repeat for each Lot.Run group   #####
dlply(Test50.df, .(Lot.Run), segmentf_df)

at this point, there’s an  error message
[28] ERROR:
object 'segmentf_df' not found

Any suggestions?
Thanks, Paul

> dput(Test50.df)
structure(list(Cycle = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L,
23L, 24L, 25L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L), Lot.Run = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("J062431-1",
"J062431-2", "J062431-3", "J062432-1", "J062432-2", "J062433-1",
"J062433-2", "J062433-3", "Lot 1-1", "Lot 1-2", "Lot 2-1", "Lot 2-2",
"Lot 2-3", "Lot 3-1", "Lot 3-2", "Lot 3-3", "P041231-1", "P041231-2",
"P041531-1", "P041531-2", "P041531-3", "P041531-4"), class = "factor"),
    deltaWgt = c(38.69, 42.58, 40.95, 42.26, 40.63, 41.61, 36.73,
    41.28, 39.98, 40.63, 39.66, 39.98, 40.95, 38.36, 39.01, 39,
    38.03, 39.66, 37.7, 39.66, 40.63, 38.03, 37.71, 36.73, 37.7,
    45.18, 41.93, 42.59, 39.98, 40.95, 42.91, 38.03, 40.96, 39,
    41.61, 39.33, 43.88, 39.98, 38.68, 38.68, 36.08, 39.99, 38.35,
    40.31, 40.63, 38.68, 37.05, 38.36, 35.43, 36.73)), .Names = c("Cycle",
"Lot.Run", "deltaWgt"), row.names = c(1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 207L, 208L, 209L, 210L, 211L, 212L,
213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L, 222L, 223L,
224L, 225L, 226L, 227L, 228L, 229L, 230L, 231L), class = "data.frame")




Paul Prew   ▪  Statistician
651-795-5942   ▪   fax 651-204-7504
Ecolab Research Center   ▪  Mail Stop ESC-F4412-A
655 Lone Oak Drive   ▪   Eagan, MN 55121-1560




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