Dear All,
I am trying to put some Confidence intervals on some regressions from a linear
model with no luck. I can extract the fitted values using 'predict',
but am having difficulty in getting at the confidence intervals, or the standard
errors.
Any suggestions would be welcome
Cheers
Guy
Using Version 2.1.0 (2005-04-18) on a PC
vol.mod3 <- lm(log.volume~log.area*lake,data=vol)
summary(vol.mod3)
plot(c(1.3,2.5),c(-0.7,0.45),type="n",xlab="Log
area",ylab="Log volume")
areapred.a <- seq(min(vol$log.area[vol$lake=="a"]),
max(vol$log.area[vol$lake=="a"]), length=100)
areapred.b <- seq(min(vol$log.area[vol$lake=="b"]),
max(vol$log.area[vol$lake=="b"]), length=100)
preda <- predict(vol.mod3,
data.frame(log.area=areapred.a,interval="confidence"
,lake=rep("a",100)))
#This gives the fitted values as predicted, but no CIs> preda
1 2 3 4 5 6
7 8 9
-0.562577529 -0.553263576 -0.543949624 -0.534635671 -0.525321718 -0.516007765
-0.506693813 -0.497379860 -0.488065907
10 11 12 13 14 15
16 17 18
-0.478751955 -0.469438002 -0.460124049 -0.450810097 -0.441496144 -0.432182191
-0.422868239 -0.413554286 -0.404240333
19 20 21 22 23 24
25 26 27
-0.394926380 -0.385612428 -0.376298475 ETC ETC
#As does this, but with no SEs> preda <- predict(vol.mod3, data.frame(log.area=areapred.a,se.fit=T
,lake=rep("a",100)))
> preda
1 2 3 4 5 6
7 8 9 10
-0.562577529 -0.553263576 -0.543949624 -0.534635671 -0.525321718 -0.516007765
-0.506693813 -0.497379860 -0.488065907 -0.478751955
11 12 13 14 15 16
17 18 19 20
-0.469438002 -0.460124049 -0.450810097 ETC ETC
--------------------------------------------------------
Guy J Forrester
Biometrician
Manaaki Whenua - Landcare Research
PO Box 69, Lincoln, New Zealand.
Tel. +64 3 325 6701 x3738
Fax +64 3 325 2418
E-mail ForresterG at LandcareResearch.co.nz
www.LandcareResearch.co.nz
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
WARNING: This email and any attachments may be confidential ...{{dropped}}
"Guy Forrester" <ForresterG at landcareresearch.co.nz> writes:> Dear All, > > > I am trying to put some Confidence intervals on some regressions from a linear model with no luck. I can extract the fitted values using 'predict', but am having difficulty in getting at the confidence intervals, or the standard errors. > > Any suggestions would be welcomehelp(predict.lm) should get you there soon enough. -- O__ ---- Peter Dalgaard ??ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
At 08:40 AM 12/07/2005, Guy Forrester wrote:>Dear All, > > >I am trying to put some Confidence intervals on some regressions from a >linear model with no luck. I can extract the fitted values using >'predict', but am having difficulty in getting at the confidence >intervals, or the standard errors. > >Any suggestions would be welcome > >Cheers > >Guy > >Using Version 2.1.0 (2005-04-18) on a PC > > > > >vol.mod3 <- lm(log.volume~log.area*lake,data=vol) >summary(vol.mod3) > >plot(c(1.3,2.5),c(-0.7,0.45),type="n",xlab="Log area",ylab="Log volume") > >areapred.a <- seq(min(vol$log.area[vol$lake=="a"]), >max(vol$log.area[vol$lake=="a"]), length=100) >areapred.b <- seq(min(vol$log.area[vol$lake=="b"]), >max(vol$log.area[vol$lake=="b"]), length=100) > > >preda <- predict(vol.mod3, >data.frame(log.area=areapred.a,interval="confidence" ,lake=rep("a",100)))You have interval="confidence" inside your call to data.frame, not inside your call to predict. Hence you are creating a data frame with a variable called interval, with one level called confidence, and predict does not see interval="confidence" at all! See ?predict.lm. HTH, Simon.>#This gives the fitted values as predicted, but no CIs > > preda > 1 2 3 4 5 > 6 7 8 9 >-0.562577529 -0.553263576 -0.543949624 -0.534635671 -0.525321718 >-0.516007765 -0.506693813 -0.497379860 -0.488065907 > 10 11 12 13 14 > 15 16 17 18 >-0.478751955 -0.469438002 -0.460124049 -0.450810097 -0.441496144 >-0.432182191 -0.422868239 -0.413554286 -0.404240333 > 19 20 21 22 23 > 24 25 26 27 >-0.394926380 -0.385612428 -0.376298475 ETC ETC > >#As does this, but with no SEs > > preda <- predict(vol.mod3, data.frame(log.area=areapred.a,se.fit=T > ,lake=rep("a",100))) > > preda > 1 2 3 4 5 > 6 7 8 9 10 >-0.562577529 -0.553263576 -0.543949624 -0.534635671 -0.525321718 >-0.516007765 -0.506693813 -0.497379860 -0.488065907 -0.478751955 > 11 12 13 14 15 > 16 17 18 19 20 >-0.469438002 -0.460124049 -0.450810097 ETC ETC > > > > >-------------------------------------------------------- >Guy J Forrester >Biometrician >Manaaki Whenua - Landcare Research >PO Box 69, Lincoln, New Zealand. >Tel. +64 3 325 6701 x3738 >Fax +64 3 325 2418 >E-mail ForresterG at LandcareResearch.co.nz >www.LandcareResearch.co.nz > > >++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ >WARNING: This email and any attachments may be confidential ...{{dropped}} > >______________________________________________ >R-help at stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html