# Random Relabelling

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## Random Relabelling

 I have 4000 observations that I need to randomly relabel 1000 times and then calculate the mean of the 1000 values at each of the 4000 points.  Any ideas for where to begin? Thanks Kevin
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## Re: Random Relabelling

 Can you explain this a bit more. At the moment I don't see what you are trying to achieve.   "calculate the mean of the 1000 values at each of the 4000 points" does not seem to make sense. --- On Wed, 4/20/11, kmatthews <[hidden email]> wrote: > From: kmatthews <[hidden email]> > Subject: [R] Random Relabelling > To: [hidden email] > Received: Wednesday, April 20, 2011, 10:04 AM > I have 4000 observations that I need > to randomly relabel 1000 times and then > calculate the mean of the 1000 values at each of the 4000 > points.  Any ideas > for where to begin? > > Thanks > Kevin > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 I have a map of Iowa of with 4000 locations.  At each location, I have a cancer mortality rate.  I need to test my null hypothesis; that the spatial distribution of the mortality rates is  random.  For this test, I need to establish a spatial reference distribution. My reference distribution will be created by some random relabelling algorithm.  The 4000 locations would remain fixed, but the observed mortality rates would be randomly redistributed.  Then, I want 1000 permutations of the same algorithm.  For each of those 1000 times, I would record the redistributed mortality rate at each location.  Then,  I would calculate the mean of the 1000 points.  The result would be a spatial reference distribution with a mean value of the random permutations at each of the 4000 locations. Thanks for the response, Kevin On Wed, Apr 20, 2011 at 11:08 AM, John Kane <[hidden email]> wrote: > Can you explain this a bit more. At the moment I don't see what you are > trying to achieve.   "calculate the mean of the 1000 values at each of the > 4000 points" does not seem to make sense. > > --- On Wed, 4/20/11, kmatthews <[hidden email]> wrote: > > > From: kmatthews <[hidden email]> > > Subject: [R] Random Relabelling > > To: [hidden email] > > Received: Wednesday, April 20, 2011, 10:04 AM > > I have 4000 observations that I need > > to randomly relabel 1000 times and then > > calculate the mean of the 1000 values at each of the 4000 > > points.  Any ideas > > for where to begin? > > > > Thanks > > Kevin > > > >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 There is probably a better way to do this but a for loop like this should work. You would just need to change the numbers to yours and then add on the locations ========================================================= scores  <- 1:5 mydata <- matrix(data=NA, nrow=5, ncol=10) for(i in 1:10) { mydata[,i] <- sample(scores, 5, replace=FALSE) } ========================================================= --- On Wed, 4/20/11, Kevin Matthews <[hidden email]> wrote: From: Kevin Matthews <[hidden email]> Subject: Re: [R] Random Relabelling To: "John Kane" <[hidden email]> Cc: [hidden email] Received: Wednesday, April 20, 2011, 1:22 PM I have a map of Iowa of with 4000 locations.  At each location, I have a cancer mortality rate.  I need to test my null hypothesis; that the spatial distribution of the mortality rates is  random.  For this test, I need to establish a spatial reference distribution.   My reference distribution will be created by some random relabelling algorithm.  The 4000 locations would remain fixed, but the observed mortality rates would be randomly redistributed.  Then, I want 1000 permutations of the same algorithm.  For each of those 1000 times, I would record the redistributed mortality rate at each location.  Then,  I would calculate the mean of the 1000 points.  The result would be a spatial reference distribution with a mean value of the random permutations at each of the 4000 locations.   Thanks for the response,Kevin On Wed, Apr 20, 2011 at 11:08 AM, John Kane <[hidden email]> wrote: Can you explain this a bit more. At the moment I don't see what you are trying to achieve.   "calculate the mean of the 1000 values at each of the 4000 points" does not seem to make sense. --- On Wed, 4/20/11, kmatthews <[hidden email]> wrote: > From: kmatthews <[hidden email]> > Subject: [R] Random Relabelling > To: [hidden email] > Received: Wednesday, April 20, 2011, 10:04 AM > I have 4000 observations that I need > to randomly relabel 1000 times and then > calculate the mean of the 1000 values at each of the 4000 > points.  Any ideas > for where to begin? > > Thanks > Kevin >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 Kevin, The following follows John's suggestion, but without the loop.  It's quick for me. Jeremy Jeremy T. Hetzel Boston University ## Generate sample data n <- 4000 rep <- 1000 rate <- rnorm(n, mean = 15, sd = 2) / 100000 # Mortality rates around 15/100k ## Create an empty matrix with appropriate dimensions permutations <- matrix(ncol = n, nrow = rep) ## Use apply() to resample permutations <- apply(permutations, 1, function(x) { sample(rate, size = n, replace = F) }) ## Look at the matrix dim(permutations) head(permutations) ## Find the column means means <- apply(permutations, 1, mean) means On Wednesday, April 20, 2011 1:56:35 PM UTC-4, John Kane wrote: > > There is probably a better way to do this but a for loop like this should > work. You would just need to change the numbers to yours and then add on the > locations > ========================================================= > > scores  <- 1:5 > mydata <- matrix(data=NA, nrow=5, ncol=10) > > for(i in 1:10) { > mydata[,i] <- sample(scores, 5, replace=FALSE) > } > > ========================================================= > --- On Wed, 4/20/11, Kevin Matthews <[hidden email]> wrote: > > From: Kevin Matthews <[hidden email]> > Subject: Re: [R] Random Relabelling > To: "John Kane" <[hidden email]> > Cc: [hidden email] > Received: Wednesday, April 20, 2011, 1:22 PM > > I have a map of Iowa of with 4000 locations.  At each location, I have a > cancer mortality rate.  I need to test my null hypothesis; that the spatial > distribution of the mortality rates is  random.  For this test, I need to > establish a spatial reference distribution.   > > > My reference distribution will be created by some random relabelling > algorithm.  The 4000 locations would remain fixed, but the observed > mortality rates would be randomly redistributed.  Then, I want 1000 > permutations of the same algorithm.  For each of those 1000 times, I would > record the redistributed mortality rate at each location.  Then,  I would > calculate the mean of the 1000 points.  The result would be a spatial > reference distribution with a mean value of the random permutations at each > of the 4000 locations.   > > Thanks for the response,Kevin > > On Wed, Apr 20, 2011 at 11:08 AM, John Kane <[hidden email]> wrote: > > > Can you explain this a bit more. At the moment I don't see what you are > trying to achieve.   "calculate the mean of the 1000 values at each of the > 4000 points" does not seem to make sense. > > --- On Wed, 4/20/11, kmatthews <[hidden email]> wrote: > > > From: kmatthews <[hidden email]> > > > Subject: [R] Random Relabelling > > > To: [hidden email] > > > Received: Wednesday, April 20, 2011, 10:04 AM > > > I have 4000 observations that I need > > > to randomly relabel 1000 times and then > > > calculate the mean of the 1000 values at each of the 4000 > > > points.  Any ideas > > > for where to begin? > > > > > > Thanks > > > Kevin > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] 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. > >______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code. Jeremy T. Hetzel Boston University
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## Re: Random Relabelling

 In reply to this post by kmatthews Hi: How about y <- rnorm(4000) ymat <- rowMeans(replicate(1000, y[sample(4000)])) hist(ymeans) system.time({y <- rnorm(4000); yy <- rowMeans(replicate(1000, y[sample(4000)]))})    user  system elapsed    0.19    0.03    0.22 HTH, Dennis On Wed, Apr 20, 2011 at 7:04 AM, kmatthews <[hidden email]> wrote: > I have 4000 observations that I need to randomly relabel 1000 times and then > calculate the mean of the 1000 values at each of the 4000 points.  Any ideas > for where to begin? > > Thanks > Kevin > > -- > View this message in context: http://r.789695.n4.nabble.com/Random-Relabelling-tp3463100p3463100.html> Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > [hidden email] 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. > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 In reply to this post by jthetzel I KNEW there was a better way! --- On Wed, 4/20/11, Jeremy Hetzel <[hidden email]> wrote: > From: Jeremy Hetzel <[hidden email]> > Subject: Re: [R] Random Relabelling > To: [hidden email] > Cc: [hidden email], "Kevin Matthews" <[hidden email]> > Received: Wednesday, April 20, 2011, 2:25 PM > Kevin, > > The following follows John's suggestion, but without the > loop.  It's quick > for me. > > Jeremy > > > Jeremy T. Hetzel > Boston University > > > > ## Generate sample data > n <- 4000 > rep <- 1000 > rate <- rnorm(n, mean = 15, sd = 2) / 100000 # Mortality > rates around > 15/100k > > ## Create an empty matrix with appropriate dimensions > permutations <- matrix(ncol = n, nrow = rep) > > ## Use apply() to resample > permutations <- apply(permutations, 1, function(x) > { > sample(rate, size = n, replace = F) > }) > > ## Look at the matrix > dim(permutations) > head(permutations) > > ## Find the column means > means <- apply(permutations, 1, mean) > means > > > > > > On Wednesday, April 20, 2011 1:56:35 PM UTC-4, John Kane > wrote: > > > > There is probably a better way to do this but a for > loop like this should > > work. You would just need to change the numbers to > yours and then add on the > > locations > > > ========================================================= > > > > scores  <- 1:5 > > mydata <- matrix(data=NA, nrow=5, ncol=10) > > > > for(i in 1:10) { > > mydata[,i] <- sample(scores, 5, replace=FALSE) > > } > > > > > ========================================================= > > --- On Wed, 4/20/11, Kevin Matthews <[hidden email]> > wrote: > > > > From: Kevin Matthews <[hidden email]> > > Subject: Re: [R] Random Relabelling > > To: "John Kane" <[hidden email]> > > Cc: [hidden email] > > Received: Wednesday, April 20, 2011, 1:22 PM > > > > I have a map of Iowa of with 4000 locations.  At > each location, I have a > > cancer mortality rate.  I need to test my null > hypothesis; that the spatial > > distribution of the mortality rates is  > random.  For this test, I need to > > establish a spatial reference distribution.  > > > > > > My reference distribution will be created by some > random relabelling > > algorithm.  The 4000 locations would remain > fixed, but the observed > > mortality rates would be randomly redistributed.  > Then, I want 1000 > > permutations of the same algorithm.  For each of > those 1000 times, I would > > record the redistributed mortality rate at each > location.  Then,  I would > > calculate the mean of the 1000 points.  The > result would be a spatial > > reference distribution with a mean value of the random > permutations at each > > of the 4000 locations.  > > > > Thanks for the response,Kevin > > > > On Wed, Apr 20, 2011 at 11:08 AM, John Kane <[hidden email]> > wrote: > > > > > > Can you explain this a bit more. At the moment I don't > see what you are > > trying to achieve.   "calculate the > mean of the 1000 values at each of the > > 4000 points" does not seem to make sense. > > > > --- On Wed, 4/20/11, kmatthews <[hidden email]> > wrote: > > > > > From: kmatthews <[hidden email]> > > > > > Subject: [R] Random Relabelling > > > > > To: [hidden email] > > > > > Received: Wednesday, April 20, 2011, 10:04 AM > > > > > I have 4000 observations that I need > > > > > to randomly relabel 1000 times and then > > > > > calculate the mean of the 1000 values at each of > the 4000 > > > > > points.  Any ideas > > > > > for where to begin? > > > > > > > > > > Thanks > > > > > Kevin > > > > > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > [hidden email] > 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. > > > > > -----Inline Attachment Follows----- > > ______________________________________________ > [hidden email] > 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. > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 On 2011-04-23 03:42, John Kane wrote: > I KNEW there was a better way! > > --- On Wed, 4/20/11, Jeremy Hetzel<[hidden email]>  wrote: > >> From: Jeremy Hetzel<[hidden email]> >> Subject: Re: [R] Random Relabelling >> To: [hidden email] >> Cc: [hidden email], "Kevin Matthews"<[hidden email]> >> Received: Wednesday, April 20, 2011, 2:25 PM >> Kevin, >> >> The following follows John's suggestion, but without the >> loop.  It's quick >> for me. >> >> Jeremy >> >> >> Jeremy T. Hetzel >> Boston University >> >> >> >> ## Generate sample data >> n<- 4000 >> rep<- 1000 >> rate<- rnorm(n, mean = 15, sd = 2) / 100000 # Mortality >> rates around >> 15/100k >> >> ## Create an empty matrix with appropriate dimensions >> permutations<- matrix(ncol = n, nrow = rep) >> >> ## Use apply() to resample >> permutations<- apply(permutations, 1, function(x) >> { >> sample(rate, size = n, replace = F) >> }) >> >> ## Look at the matrix >> dim(permutations) >> head(permutations) >> >> ## Find the column means >> means<- apply(permutations, 1, mean) >> means >> And you might note that   means <- rowMeansy(permutations) is about 10-15 times faster (if speed matters). Peter Ehlers [...snipped...] ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 In reply to this post by jthetzel Thanks to everyone... this helps a lot.  Just a quick question about etiquette in this forum (as it my first time questioning)... are notes of gratitude usually given in these forums?  On Wed, Apr 20, 2011 at 1:26 PM, jthetzel [via R] wrote: Kevin, The following follows John's suggestion, but without the loop.  It's quick for me. Jeremy Jeremy T. Hetzel Boston University ## Generate sample data n <- 4000 rep <- 1000 rate <- rnorm(n, mean = 15, sd = 2) / 100000 # Mortality rates around 15/100k ## Create an empty matrix with appropriate dimensions permutations <- matrix(ncol = n, nrow = rep) ## Use apply() to resample permutations <- apply(permutations, 1, function(x) { sample(rate, size = n, replace = F) }) ## Look at the matrix dim(permutations) head(permutations) ## Find the column means means <- apply(permutations, 1, mean) means On Wednesday, April 20, 2011 1:56:35 PM UTC-4, John Kane wrote: > > There is probably a better way to do this but a for loop like this should > work. You would just need to change the numbers to yours and then add on the > locations > ========================================================= > > scores  <- 1:5 > mydata <- matrix(data=NA, nrow=5, ncol=10) > > for(i in 1:10) { > mydata[,i] <- sample(scores, 5, replace=FALSE) > } > > ========================================================= > --- On Wed, 4/20/11, Kevin Matthews <[hidden email]> wrote: > > From: Kevin Matthews <[hidden email]> > Subject: Re: [R] Random Relabelling > To: "John Kane" <[hidden email]> > Cc: [hidden email] > Received: Wednesday, April 20, 2011, 1:22 PM > > I have a map of Iowa of with 4000 locations.  At each location, I have a > cancer mortality rate.  I need to test my null hypothesis; that the spatial > distribution of the mortality rates is  random.  For this test, I need to > establish a spatial reference distribution.   > > > My reference distribution will be created by some random relabelling > algorithm.  The 4000 locations would remain fixed, but the observed > mortality rates would be randomly redistributed.  Then, I want 1000 > permutations of the same algorithm.  For each of those 1000 times, I would > record the redistributed mortality rate at each location.  Then,  I would > calculate the mean of the 1000 points.  The result would be a spatial > reference distribution with a mean value of the random permutations at each > of the 4000 locations.   > > Thanks for the response,Kevin > > On Wed, Apr 20, 2011 at 11:08 AM, John Kane <[hidden email]> wrote: > > > Can you explain this a bit more. At the moment I don't see what you are > trying to achieve.   "calculate the mean of the 1000 values at each of the > 4000 points" does not seem to make sense. > > --- On Wed, 4/20/11, kmatthews <[hidden email]> wrote: > > > From: kmatthews <[hidden email]> > > > Subject: [R] Random Relabelling > > > To: [hidden email] > > > Received: Wednesday, April 20, 2011, 10:04 AM > > > I have 4000 observations that I need > > > to randomly relabel 1000 times and then > > > calculate the mean of the 1000 values at each of the 4000 > > > points.  Any ideas > > > for where to begin? > > > > > > Thanks > > > Kevin > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] 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. > >______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Jeremy T. Hetzel Boston University If you reply to this email, your message will be added to the discussion below: http://r.789695.n4.nabble.com/Random-Relabelling-tp3463100p3463799.html To unsubscribe from Random Relabelling, click here.
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## Re: Random Relabelling

 On Apr 25, 2011, at 10:53 AM, kmatthews wrote: > Thanks to everyone... this helps a lot.  Just a quick question about > etiquette in this forum (as it my first time questioning)... are   > notes of > gratitude usually given in these forums? The practice varies, some people do appreciate it. Doing so when one   is not subscribed, however, adds many additional mouse-maneuvers to   the moderator workload, ...  wasted time in my opinion. I would   suggest a private thank you message in that instance (or even more to   be preferred ... subscribing.) -- David. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Random Relabelling

 In reply to this post by kmatthews --- On Mon, 4/25/11, kmatthews <[hidden email]> wrote: > From: kmatthews <[hidden email]> > Subject: Re: [R] Random Relabelling > To: [hidden email] > Received: Monday, April 25, 2011, 10:53 AM > Thanks to everyone... this helps a > lot.  Just a quick question about > etiquette in this forum (as it my first time > questioning)... are notes of > gratitude usually given in these forums? Certainly and thanks > > On Wed, Apr 20, 2011 at 1:26 PM, jthetzel [via R] < > [hidden email]> > wrote: > > > Kevin, > > > > The following follows John's suggestion, but without > the loop.  It's quick > > for me. > > > > Jeremy > > > > > > Jeremy T. Hetzel > > Boston University > > > > > > > > ## Generate sample data > > n <- 4000 > > rep <- 1000 > > rate <- rnorm(n, mean = 15, sd = 2) / 100000 # > Mortality rates around > > 15/100k > > > > ## Create an empty matrix with appropriate dimensions > > permutations <- matrix(ncol = n, nrow = rep) > > > > ## Use apply() to resample > > permutations <- apply(permutations, 1, function(x) > > { > > sample(rate, size = n, replace = F) > > }) > > > > ## Look at the matrix > > dim(permutations) > > head(permutations) > > > > ## Find the column means > > means <- apply(permutations, 1, mean) > > means > > > > > > > > > > > > On Wednesday, April 20, 2011 1:56:35 PM UTC-4, John > Kane wrote: > > > > > > > > There is probably a better way to do this but a > for loop like this should > > > > > work. You would just need to change the numbers > to yours and then add on > > the > > > locations > > > > ========================================================= > > > > > > scores  <- 1:5 > > > mydata <- matrix(data=NA, nrow=5, ncol=10) > > > > > > for(i in 1:10) { > > > mydata[,i] <- sample(scores, 5, > replace=FALSE) > > > } > > > > > > > ========================================================= > > > --- On Wed, 4/20/11, Kevin Matthews <[hidden > email]> > > wrote: > > > > > > From: Kevin Matthews <[hidden email]> > > > > > Subject: Re: [R] Random Relabelling > > > To: "John Kane" <[hidden email]> > > > > > Cc: [hidden email] > > > Received: Wednesday, April 20, 2011, 1:22 PM > > > > > > I have a map of Iowa of with 4000 > locations.  At each location, I have a > > > cancer mortality rate.  I need to test my > null hypothesis; that the > > spatial > > > distribution of the mortality rates is  > random.  For this test, I need to > > > > > establish a spatial reference distribution. > > > > > > > > > My reference distribution will be created by some > random relabelling > > > algorithm.  The 4000 locations would remain > fixed, but the observed > > > mortality rates would be randomly > redistributed.  Then, I want 1000 > > > permutations of the same algorithm.  For > each of those 1000 times, I > > would > > > record the redistributed mortality rate at each > location.  Then,  I would > > > > > calculate the mean of the 1000 points.  The > result would be a spatial > > > reference distribution with a mean value of the > random permutations at > > each > > > of the 4000 locations. > > > > > > Thanks for the response,Kevin > > > > > > On Wed, Apr 20, 2011 at 11:08 AM, John Kane > <[hidden email]> > > wrote: > > > > > > > > > Can you explain this a bit more. At the moment I > don't see what you are > > > trying to achieve.   "calculate > the mean of the 1000 values at each of > > the > > > 4000 points" does not seem to make sense. > > > > > > --- On Wed, 4/20/11, kmatthews <[hidden > email]> > > wrote: > > > > > > > From: kmatthews <[hidden email]> > > > > > > > > > Subject: [R] Random Relabelling > > > > > > > To: [hidden email] > > > > > > > Received: Wednesday, April 20, 2011, 10:04 > AM > > > > > > > I have 4000 observations that I need > > > > > > > to randomly relabel 1000 times and then > > > > > > > calculate the mean of the 1000 values at > each of the 4000 > > > > > > > points.  Any ideas > > > > > > > for where to begin? > > > > > > > > > > > > > > Thanks > > > > > > > Kevin > > > > > > > > > > > > > > > > [[alternative HTML version deleted]] > > > > > > ______________________________________________ > > > [hidden email]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. > > > > > > > > ______________________________________________ > > [hidden email]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. > > Jeremy T. Hetzel > > Boston University > > > > > > ------------------------------ > >  If you reply to this email, your message will be > added to the discussion > > below: > > http://r.789695.n4.nabble.com/Random-Relabelling-tp3463100p3463799.html> >  To unsubscribe from Random Relabelling, click > here< > > > > > > > -- > View this message in context: http://r.789695.n4.nabble.com/Random-Relabelling-tp3463100p3473298.html> Sent from the R help mailing list archive at Nabble.com. >     [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] > 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. > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.