Error In Lm.fitx Y Offset = Offset
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y, offset = offset, singular.ok = singular.ok, …) up vote 2 down vote favorite I try a regression with R. I have the following code with no problem in importing the CSV file dat <- read.csv('http://pastebin.com/raw.php?i=EWsLjKNN',sep=";") dat # OK Works fine Regdata <- lm(Y~.,na.action=na.omit, data=dat) summary(Regdata) However when I try a regression it's not working. I get an error message: Erreur dans lm.fit(x, y, offset = offset, r lm na values singular.ok = singular.ok, ...) : aucun cas ne contient autre chose que des valeurs manquantes (NA) All my CSV file are numbers and if a "cell" is empty I have the "NA" value. Some column are not empty and some other row are sometimes empty witht the NA value... So, I don't understand why I get an error message even with : na.action=na.omit PS:Data of the CSV are available at: http://pastebin.com/EWsLjKNN r linear-regression lm share|improve this question edited Dec 19 '12 at 18:36 Brandon Bertelsen 18.9k1883170 asked Dec 19 '12 at 18:26 Swiss12000 68141126 You might want to take a look at Faraway's (free!) book: cran.r-project.org/doc/contrib/Faraway-PRA.pdf –Ricardo Saporta Dec 19 '12 at 20:20 thanks a lot the suggested book is exactely what i needed ;) –Swiss12000 Dec 22 '12 at 5:06 add a comment| 2 Answers 2 active oldest votes up vote 3 down vote You get this error message because all your data frame rows contain al least one missing value. It can be checked for example with this code: apply(data,1,function(x) sum(is.na(x))) [1] 128 126 82 78 73 65 58 34 31 30 28 30 20 21 12 20 17 16 12
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Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping trycatch r each other. Join them; it only takes a minute: Sign up Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, …) 0 non-na cases (moult package) up vote -1 down vote favorite I'm new to R and http://stackoverflow.com/questions/13958722/r-linear-regression-issue-lm-fitx-y-offset-offset-singular-ok-singular don't understand much about how it works. I'm trying to run this code however the "Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases" constantly appears and my data actually has no NA. So what should I do? > library("moult") > > mym = read.csv("Test.csv", sep=";", head=T) > head(mym) Age Sex MoultPresence Score Prim Habitat Jul.Day 1 Adult 1 1 5554210000 22 Beach 123 2 Adult 2 1 5555321000 26 Estuary http://stackoverflow.com/questions/36535483/error-in-lm-fitx-y-offset-offset-singular-ok-singular-ok-0-non-na-ca 124 3 Adult 1 1 5555553200 35 Estuary 124 4 Adult 1 1 4440000000 12 Beach 126 5 Adult 2 1 5555532100 31 Mudflat 127 6 Adult 1 1 5555321000 26 Mudflat 127 > if (is.numeric(mym$Prim)) {scores <- format(mym$Prim, scientific = FALSE, trim = TRUE)} else {scores <- mym$Prim} > mscores <- substr(scores, 1, 9) > mym$Date <- date2days(mym$Date, dateformat = "dd-mm-yyyy", startmonth = 9) > m88.2 <- moult(Prim ~ Jul.Day, data = mym) Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases > summary(m88.2) Error in summary(m88.2) : object 'm88.2' not found > m88c <- moult(Prim ~ Jul.Day, data = mym, type = 3) Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases > summary(m88c) Error in summary(m88c) : object 'm88c' not found > durationmean2ab <- function(duration, mean) { + ab <- c(-mean/duration, 1/duration) + names(ab) <- c("intercept", "slope") + return(ab) + } > uz1 <- durationmean2ab(coef(m88c, "duration"), coef(m88c, "mean")) Error in coef(m88c, "mean") : object 'm88c' not found > > ssex <- ifelse(mym$Sex == 1 | mym$Sex == 3, "male", ifelse(mym$Sex == 2 | mym$Sex == 4, "female", NA)) > mym$ssex <- as.factor(ssex) > mmf <- moult(Prim ~ Jul.Day | ssex | ssex, data = mym, type = 3) Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) c
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting http://stackoverflow.com/questions/16232650/error-in-lm-fitx-y-offset-offset-singular-ok-singular-ok-0-non ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a https://github.com/rietho/IPO/issues/6 minute: Sign up Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, …) : 0 (non-NA) cases [on hold] up vote 0 down vote favorite I encounter a problem when I use lm together with loop. I want to fit error in regression lines with every four values of xx and yy. Here is my code, >xx<-c(0 , 55, 146, 457, 643, 825,1008) >yy<-c(NA, 110, 132, 108, 124, 115, 134) >n<-length(xx) >slop<-rep(NA,n) >for (i in 4:n){ x<-xx[i-3:i] y<-yy[i-3:i] slop[i]<-lm(y~x)$coefficients[2] } Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases Could anyone please tell me why this happen? I try to do it manually, pick every four values of xx and yy and use lm, then R runs successfully. y offset = r for-loop lm share|improve this question edited Apr 26 '13 at 12:21 Jilber 30.5k44572 asked Apr 26 '13 at 9:08 fiona 111 put on hold as off-topic by Zheyuan Li, jogo, hrbrmstr, Andreas, CharithJ Oct 8 at 11:32 This question appears to be off-topic. The users who voted to close gave this specific reason:"This question was caused by a problem that can no longer be reproduced or a simple typographical error. While similar questions may be on-topic here, this one was resolved in a manner unlikely to help future readers. This can often be avoided by identifying and closely inspecting the shortest program necessary to reproduce the problem before posting." – Zheyuan Li, jogo, hrbrmstr, Andreas, CharithJIf this question can be reworded to fit the rules in the help center, please edit the question. I finally find the error and maybe it's helpful for someone who has same confusion. t<-i-3 is needed in loop, or else when i take value larger than 6, then R get confused and stop to do the calculation. –fiona Apr 26 '13 at 9:41 add a comment| 2 Answers 2 active oldest votes up vote 1 down vote Changing [i-3:i] to [(i-3):i] eliminates the error message. share|improve this answer answered Apr 26 '13 at 9:22 sieste 2,370925 add a comment| up vote 1 down vote The reason is because of operator prioriy (between - and :) it is not doing what you expect: For the first itera
Sign in Pricing Blog Support Search GitHub This repository Watch 9 Star 8 Fork 11 rietho/IPO Code Issues 13 Pull requests 0 Projects 0 Wiki Pulse Graphs New issue Error in lm.fit() when optimising group/retcor #6 Open sneumann opened this Issue Mar 19, 2015 · 2 comments Projects None yet Labels None yet Milestone No milestone Assignees No one assigned 2 participants Collaborator sneumann commented Mar 19, 2015 Hi, I get Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases when doing: > retcorGroupParameters <- getDefaultRetGroupStartingParams() > retcorGroupParameters$profStep <- 1 > resultRetcorGroup <- optimizeRetGroup(xset=mtblsSets[["negative"]], + params=retcorGroupParameters, + nSlaves=12, subdir="rsmDirectory") starting new DoE with: $distFunc [1] "cor_opt" $gapInit [1] 0.0 0.4 $gapExtend [1] 2.1 2.7 $profStep [1] 1 $plottype [1] "none" $response [1] 1 $factorDiag [1] 2 $factorGap [1] 1 $localAlignment [1] 0 $bw [1] 22 38 $minfrac [1] 0.3 0.7 $mzwid [1] 0.015 0.035 $minsamp [1] 1 $max [1] 50 $center [1] 86 Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases In addition: Warning messages: 1: closing unused connection 6 (<-localhost:11147) 2: closing unused connection 5 (<-localhost:11147) 3: closing unused connection 4 (<-localhost:11147) 4: closing unused connection 3 (<-localhost:11147) Traceback shows: > traceback() 9: stop("0 (non-NA) cases") 8: lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) 7: lm(formula = resp ~ FO(x1, x2, x3, x4, x5) + TWI(x1, x2, x3, x4, x5) + PQ(x1, x2, x3, x4, x5), data = design) 6: eval(expr, envir, enclos) 5: eval(CALL, parent.frame()) 4: rsm(formula, data = design) 3: createModel(retcor_result$design, params$to_o