On Jan 23, 2013, at 5:45 AM, Simonas Kecorius wrote:
I found a code:
y.ts <- ts(data, frequency=12)
aggregate(y.ts, FUN=quantile, probs=0.10)
Seems it works fine even for a big data.frame.
Except for the fact that 'y.ts' is not a dataframe, so you are using a
function that has different arguments than `aggregate.data.frame`.
With the `ts` call you implicitly constructed `ts(data.matrix(data),
frequency=12)` and will be getting quantile estimates on groups of 12,
which is not at all what you asked for in the first place.
--
David.
Thanks for your help.
2013/1/22 David Winsemius <dwinsem...@comcast.net>
On Jan 22, 2013, at 5:58 AM, Simonas Kecorius wrote:
Hey Duncan,
Neither me do imagine what formula OpenOffice uses for quantiles. I
have
checked a data string, 24 values, to calculate a quantiles with
OpenOffice
and R. The result is identical. The problem arises when I try to
implement
quantile calculation in this form:
dat2<-with(dat1,aggregate(cbind(dat1[,
1:71]),by=list(newID),quantiles,0.1,type=4))
. This code does not generate an error, but I guess neither a right
result.
You guess? What result and what is "right"?
So my question would be:
How I could calculate quantiles for a big data.frame in R (71
columns and
288 rows). I need to take 24 rows, calculate quantiles, then take
another
24 rows etc..for 71 columns.
You have already been told that you are misspelling the name of the
R function.
The other open question in my mind is whether you were hoping for
something other than a single quantile (in this case the 10th
percentile, or perhaps wanted the quantiles that would divide your
data into deciles?
If you want to do the calculation within groups then the second
argument to `aggregate` must specify the grouping. By design
`aggregate` will apply the function on all columns.
--
David.
Thanks in advance.
2013/1/22 Duncan Murdoch <murdoch.dun...@gmail.com>
On 13-01-21 6:41 PM, Simonas Kecorius wrote:
Dear R users,
I came up to a problem dealing with percentiles in R.
From my previous questions: I do have a big data.frame, with lots of
columns and rows. The following command enables me to calculate
means for
all data frame.
dat1$newID<-rep(1:(nrow(dat1)/**12),each=12) #if nrow(dat1)/12 is
integer
dat2<-with(dat1,aggregate(**cbind(dat1[,1:71]),by=list(**newID),mean))
What I need is to calculate percentiles for each group (there are 12
values
in a group). I tried the following:
duomenai<-with(dat1,aggregate(**cbind(dat1[,1:71]),by=list(**
newID),quantiles,0.1,type=4))
You didn't define quantiles, so that won't work. Assuming that's a
typo,
and you meant quantile...
First, is the following syntax is right?
Secondly, I tried to calculate percentiles using OpenOffice and
there is
disagreement between values. If I do calculation for some number
row, than
R and OpenOffice numbers coincide, but for a data.frame it seams that
something goes wrong.
There are lots of different formulas for empirical quantiles. The
ones
available in R are described in the ?quantile help topic. What
formula
does OpenOffice use?
Duncan Murdoch
--
Simonas Kecorius
**
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David Winsemius, MD
Alameda, CA, USA
--
Simonas Kecorius
David Winsemius, MD
Alameda, CA, USA
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