Hi Paul, No problem.
Try: par(mfrow=c(1,2)) ldply(SP.seg,plot) #or lapply(SP.seg,plot) A.K. On Monday, October 14, 2013 5:57 PM, "Prew, Paul" <paul.p...@ecolab.com> wrote: Hello, the code provided by arun did the trick. Thank you very much, arun. However, I'm now unsure of how to further process the results . Looking at the vignette aka "split-apply-combine". It appears that I could now create a dataframe from the list of results, and then run the results through the function plot.segmented to view the piecewise regressions by the grouping variable Lot.Run. However, the list is not in the structure expected by ldply -- >SP.seg <- dlply((df,.(Lot.Run),segmentf_df) >SP.out <- ldply(SP.seg) [9] ERROR: Results must be all atomic, or all data frames >class(SP.seg)[[1]] [1] "list" >head(SP.seg) $`J062431-1` Call: segmented.lm(obj = out.lm, seg.Z = ~Cycle, psi = (Cycle = NA), control = seg.control(stop.if.error = FALSE, n.boot = 0, gap = FALSE, jt = FALSE, nonParam = TRUE)) Meaningful coefficients of the linear terms: (Intercept) Cycle U1.Cycle U2.Cycle U3.Cycle U4.Cycle U5.Cycle U6.Cycle 40.11786 -0.06664 -0.68539 0.49316 0.14955 0.03612 0.22257 -0.41166 U7.Cycle U8.Cycle U9.Cycle U10.Cycle -0.48365 0.37949 0.24945 0.06712 Estimated Break-Point(s) psi1.Cycle psi2.Cycle psi3.Cycle psi4.Cycle psi5.Cycle psi6.Cycle psi7.Cycle psi8.Cycle psi9.Cycle psi10.Cycle : 19.67 34.31 51.02 72.10 97.94 117.20 130.10 147.10 155.70 160.40 $`J062431-2` Call: segmented.lm(obj = out.lm, seg.Z = ~Cycle, psi = (Cycle = NA), control = seg.control(stop.if.error = FALSE, n.boot = 0, gap = FALSE, jt = FALSE, nonParam = TRUE)) Meaningful coefficients of the linear terms: (Intercept) Cycle U1.Cycle U2.Cycle U3.Cycle U4.Cycle U5.Cycle U6.Cycle 40.11786 -0.06664 -0.68539 0.49316 0.14955 0.03612 0.22257 -0.41166 U7.Cycle U8.Cycle U9.Cycle U10.Cycle -0.48365 0.37949 0.24945 0.06712 Estimated Break-Point(s) psi1.Cycle psi2.Cycle psi3.Cycle psi4.Cycle psi5.Cycle psi6.Cycle psi7.Cycle psi8.Cycle psi9.Cycle psi10.Cycle : 19.67 34.31 51.02 72.10 97.94 117.20 130.10 147.10 155.70 160.40 My hope was to eventually increase my understanding enough to create lattice plots using 'segment.plot' via ldply. Will that even work with the output object from this segmented package? Thanks,Paul 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 -----Original Message----- From: arun [mailto:smartpink...@yahoo.com] Sent: Saturday, October 12, 2013 1:42 AM To: R help Cc: Prew, Paul Subject: Re: [R] using ddply with segmented regression Hi, Try: segmentf_df <- function(df) { out.lm<-lm(deltaWgt~Cycle, data=df) segmented(out.lm,seg.Z=~Cycle, psi=(Cycle=NA),control=seg.control(stop.if.error=FALSE,n.boot=0)) } library(plyr) library(segmented) dlply(df,.(Lot.Run),segmentf_df) $`J062431-1` Call: segmented.lm(obj = out.lm, seg.Z = ~Cycle, psi = (Cycle = NA), control = seg.control(stop.if.error = FALSE, n.boot = 0)) Meaningful coefficients of the linear terms: (Intercept) Cycle U1.Cycle U2.Cycle 38.480 1.130 -2.760 1.497 Estimated Break-Point(s) psi1.Cycle psi2.Cycle : 3.732 5.056 $`J062431-2` Call: segmented.lm(obj = out.lm, seg.Z = ~Cycle, psi = (Cycle = NA), control = seg.control(stop.if.error = FALSE, n.boot = 0)) Meaningful coefficients of the linear terms: (Intercept) Cycle U1.Cycle U2.Cycle 48.4300 -3.2500 3.0905 -0.6555 Estimated Break-Point(s) psi1.Cycle psi2.Cycle : 2.12 22.15 attr(,"split_type") [1] "data.frame" attr(,"split_labels") Lot.Run 1 J062431-1 2 J062431-2 #or dlply(df,.(Lot.Run),function(x) segmentf_df(x)) #or lapply(split(df,df$Lot.Run,drop=TRUE),function(x) segmentf_df(x)) A.K. On Friday, October 11, 2013 11:16 PM, "Prew, Paul" <paul.p...@ecolab.com> wrote: 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 CONFIDENTIALITY NOTICE: This e-mail communication and any attachments may contain proprietary and privileged information for the use of the designated recipients named above. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. CONFIDENTIALITY NOTICE: This e-mail communication and any attachments may contain proprietary and privileged information for the use of the designated recipients named above. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
