Petr,
Thanks for your suggestions. It makes sense, since I don't know how to make
a matrix with different length of rows.
I have a concern for this problem. I actually deal with a much bigger
dataset e.g. 1000, and each dataset needs to change the number of data in it
according a vector which has 1000 corresponding different values. It will
be hard to deal with data one by one. Is there a way I can do them together?
Sorry for not making it clear.
I am thinking I have to use 'for loop' to get a list of vectors. But I am
not sure how to do it efficiently? Thanks again.
Petr Pikal wrote:
>
> Hi
>
> I have no idea how you could do what you want. I only recommend you to use
> list instead of matrix as list can incorporate objects with various size
>
> I am not sure if this is the most elegant way but you can make your matrix
> a data frame
>
> ddd<- as.data.frame(data)
> and than use thist
>
> lapply(ddd, function(x) unlist(list(x)))
>
> To get list of vectors
>
> Regards
> Petr
>
> r-help-boun...@r-project.org napsal dne 01.02.2010 03:46:34:
>
>>
>> Hello,
>>
>> This may be a rare question. I am struggling to solve it. I really
>> appreciate any help or suggestions. Thanks a lot in advance!
>>
>>
>> I put my questions between the code to make it clear. The problem I have
> is:
>> I generated 10 data sets with 8 data for each set. Now I want to change
> the
>> number of data in each dataset according to a vector 'size' (as
> follows),
>> that is, each new dataset contains different number of data. How can I
> do
>> it? After generating the new datasets, how can I seperate the data from
> two
>> distributions and calculate the sample mean? Thanks a lot.
>>
>>
>>
>> # generate 10 data sets, each data sets include 8 sample. 4 from N(0, 1)
> and
>> 4 from N(5, 1)
>> data<- matrix(0,10,8)
>> th <- c(0, 5, 1)
>> for(i in 1:10){
>> data[i,] <- rnorm(8,mean= rep(th[1:2],8/2),sd=th[3])
>> }
>>
>> # change the number of samples for each data set. e.g. the first
> dataset
>> needs to increase to 20, the #first 8 keep the same, add another 12
> sample
>> (6 from N(0,1) and the other 6 from N(5, 1) ), the second #dataset needs
> to
>> increase to 10, keep the first 8 the same, generate another 2 (one from
>> N(0,1) and the #other one from N(5,1)), the third data set does not
> need to
>> change. etc.
>>
>> size=c(20, 10, 8, 14, 16, 12, 8, 80)
>>
>>
>> # Since each data set changes to different size, and add different
> number of
>> data, for each dataset how #can I calculate the difference of the
> sample
>> mean from N(0,1) and the sample mean from
>> #N(5,1) and the pooled standard deviation of two samples. Two
> difficulties:
>> each new dataset includes #different number of data; another difficulty,
>> when I generated data, the two successive data are
>> #from different normal distribution, how can I seperate them and
> calculate
>> the average for each sample #and pooled standard deviation?
>>
>>
>>
>> --
>> View this message in context:
> http://n4.nabble.com/how-to-generate-data-set-
>> with-different-length-and-calculate-the-mean-tp1458420p1458420.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
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>> PLEASE do read the posting guide
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>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide
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>
>
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