[R] How to calculate variance on multiple numbers at once?

Thu Nov 12 15:19:58 CET 2015

Essentially the problem is related to this problem. I am measuring the
fluorescence (flu) generated over time (clock) from 5 samples (samp)
which are grouped by two targets (targ).
I can calculate the variance of the fluorescence for each sample at a
given time (in this example, for sample 1); but if I consider a target
at the time there would be multiple readings at once to consider.
would the variance formula still be OK to use.
In this example:
>>>
samp <- c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4,
5, 5, 5, 5, 5)
clock <- rep(1:5,5)
targ <- c(rep("A", 5), rep("B", 5), rep("A", 5), rep("A", 5), rep("B", 5))
flu <- c(-0.012, -0.01, -0.008, -0.002, -0.001, -0.007, -0.008,
-0.009, -0.009, -0.012, -0.002, -0.003, -0.003, 0.001, 0.002, -0.006,
-0.001, 0.001, 0.002, 0.002, -0.002, -0.003, -0.003, -0.002, -0.001)
my.data <- data.frame(well, clock, targ, flu, stringsAsFactors = FALSE)

# variance with individual numbers
sub <- subset(my.data, samp == 1)
plot(sub$flu ~ sub$clock)
abline(lm(sub$flu ~ sub$clock))
for (i in 2:nrow(sub)) {
  X <- subset(sub, clock <= i)
  V <- var(X$flu)
  cat("variance at clock ", i, " = ", V, "\n", sep="")
}
# variance with multiple numbers
sub <- subset(my.data, targ == 'A')
plot(sub$flu ~ sub$clock)
abline(lm(sub$flu ~ sub$clock))
for (i in 2:max(sub$clock)) {
  X <- subset(sub, clock <= i)
  V <- var(X$flu)
  cat("variance at clock ", i, " = ", V, "\n", sep="")
}

the results for the individual numbers are:
variance at clock 2 = 2e-06
variance at clock 3 = 4e-06
variance at clock 4 = 1.866667e-05
variance at clock 5 = 2.38e-05

while the results for the multiple numbers are:
variance at clock 2 = 2.026667e-05
variance at clock 3 = 1.911111e-05
variance at clock 4 = 2.026515e-05
variance at clock 5 = 1.995238e-05

shall I accept these latter values?
Thanks

On Thu, Nov 12, 2015 at 10:59 AM, John Kane <jrkrideau at inbox.com> wrote:
> I still don't understand what you are doing. I think we need to see your actual data and the code your are using.  If S.Ellison's post has not shown up it is below my signature.
>
> Have a look at http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html for suggestions on how to pose a question here. In particular data should be supplied in dput() format as it gives us a copy of exactly how the data is formatted on your machine.
>
>
> John Kane
> Kingston ON Canada
>
> ## ===========================================
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Luigi
>> Marongiu
>> if I have a sample set of the following numbers x1=0.09, x2=0.94, x3=0.48,
>> x4=0.74, x5=0.04 I can calculate the variance easily.
> Not without concatenating them into a vector, you can't. You need them in a vector, as in
> var( c(x1, x2, x3, x4, x5) )
>
>> But if each x is actually a subset of multiple values, what would be the formula
>> to calculate the variance? and it is possible to implement such mathematical
>> function in R?
> This is what R wants anyway, so the function you are looking for is var()
>
>> For instance if I have the following: x1=(0.77, 0.22, 0.44), x2=(0.26, 0.89, 0.58),
>> x3=(0.20, 0.25, 0.91), x4=(0.06, 0.13, 0.26) and x5=(0.65, 0.16, 0.72) how can i
>> calculate the variance for each x?
> var(x1)
> var(x2)
> ....
>
> or, if you want to be a bit more slick about it and do it in one line
>
> lapply(list( x1, x2, x3, ...), var  )
>
> (or sapply() if you want a vector result)
>
> ## ===========================================
>
>
>> -----Original Message-----
>> From: marongiu.luigi at gmail.com
>> Sent: Wed, 11 Nov 2015 23:20:26 +0000
>> To: jrkrideau at inbox.com
>> Subject: Re: [R] How to calculate variance on multiple numbers at once?
>>
>> Thank you for the reply. For clarification, let's say that I can
>> calculate the sum of variances of the individual x numbers in five
>> consecutive steps (although of course there are better
>> implementations) where each step the sum is incremented by (x -
>> mean)^2.
>> In the case I am handling, at each step i have to consider 3 values at
>> once and I don't know how to relate them neither with the mathematical
>> formula nor with the R implementation.
>> Besides I haven't seen Ellison's answer...
>> Best regards
>> L
>>
>> On Wed, Nov 11, 2015 at 1:04 PM, John Kane <jrkrideau at inbox.com> wrote:
>>> I really don't understand what you are looking for but if S. Ellison's
>>> answer is not what you want what about this where your various x vectors
>>> are in a data frame
>>>
>>> ibrary(reshape2)
>>> library(plyr)
>>>
>>> dat1  <-  structure(list(x1 = c(0.77, 0.22, 0.44), x2 = c(0.26, 0.89,
>>> 0.58
>>> ), x3 = c(0.2, 0.25, 0.91), x4 = c(0.06, 0.13, 0.26), x5 = c(0.65,
>>> 0.16, 0.72)), .Names = c("x1", "x2", "x3", "x4", "x5"), row.names =
>>> c(NA,
>>> -3L), class = "data.frame")
>>>
>>> m1  <-   melt(dat1)
>>>
>>> ddply(m1, .(variable), summarize, variance = var(value))
>>>
>>> John Kane
>>> Kingston ON Canada
>>>
>>>
>>>> -----Original Message-----
>>>> From: marongiu.luigi at gmail.com
>>>> Sent: Wed, 11 Nov 2015 11:26:25 +0000
>>>> To: r-help at r-project.org
>>>> Subject: [R] How to calculate variance on multiple numbers at once?
>>>>
>>>> Dear all,
>>>>
>>>> if I have a sample set of the following numbers x1=0.09, x2=0.94,
>>>> x3=0.48, x4=0.74, x5=0.04 I can calculate the variance easily.
>>>> But if each x is actually a subset of multiple values, what would be
>>>> the formula to calculate the variance? and it is possible to implement
>>>> such mathematical function in R?
>>>>
>>>> For instance if I have the following: x1=(0.77, 0.22, 0.44), x2=(0.26,
>>>> 0.89, 0.58), x3=(0.20, 0.25, 0.91), x4=(0.06, 0.13, 0.26) and
>>>> x5=(0.65, 0.16, 0.72) how can i calculate the variance for each x?
>>>>
>>>> Thank you
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>>> 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.
>>>
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