Hi:
One approach is to remove the top two observations from each group.
Here's one way:
ddply(mydata, .(group), function(d) tail(d, -2))
Now apply the previous procedure to this data subset.
HTH,
Dennis
On Tue, Apr 26, 2011 at 7:18 AM, Dimitri Liakhovitski
<dimitri.liakhovit...@gmail.com> wrote:
> Dennis, this is really great, thanks a lot!
> Do you know how to prevent the result from omitting the first 2
> values. I mean - it starts (within each group) with the 3rd row but
> omits the first 2...
> Dimitri
>
> On Mon, Apr 25, 2011 at 5:31 PM, Dennis Murphy <djmu...@gmail.com> wrote:
>> Hi:
>>
>> I think the embed() function is your friend here. From its help page example,
>>
>>> x <- 1:10
>>> embed (x, 3)
>> [,1] [,2] [,3]
>> [1,] 3 2 1
>> [2,] 4 3 2
>> [3,] 5 4 3
>> [4,] 6 5 4
>> [5,] 7 6 5
>> [6,] 8 7 6
>> [7,] 9 8 7
>> [8,] 10 9 8
>>
>>
>> Applying it to your test data,
>>
>> # h() creates a weighted average of the observations in each row
>> h <- function(x) embed(x, 3) %*% c(0.5, 0.35, 0.15)
>> library(plyr)
>> ddply(mydata, "group", summarise, ma = h(myvalue))
>> group ma
>> 1 group1 11.00
>> 2 group1 16.75
>> 3 group1 9.25
>> 4 group1 3.00
>> 5 group1 0.00
>> 6 group1 5.00
>> 7 group2 85.00
>> 8 group2 30.00
>> 9 group2 150.00
>> 10 group2 205.00
>> 11 group2 115.00
>> 12 group2 30.00
>>
>> Does that work for you? The rollapply() function in the zoo package
>> may also be applicable with a similar input function that computes a
>> weighted average.
>>
>> HTH,
>> Dennis
>>
>>
>> On Mon, Apr 25, 2011 at 1:50 PM, Dimitri Liakhovitski
>> <dimitri.liakhovit...@gmail.com> wrote:
>>> Hello!
>>> I wrote a piece of code below that does the job but seems too "loopy" to me.
>>> I was wondering if there is any way to make it more efficient/less "loopy"?
>>> Thanks a lot for your hints!
>>> Dimitri
>>>
>>> ### Creating example data set:
>>>
>>> mygroups<-c(rep("group1", 8),rep("group2", 8))
>>> myweeks<-seq(as.Date("2010-01-04"), length = 8, by = "week")
>>> values.w<-c(0,10,15,20,0,0,0,10,100,200,0,0,300,200,0,0)
>>> mydata<-data.frame(group=mygroups,mydates=myweeks,myvalue=values.w)
>>> mydata$group<-as.factor(mydata$group)
>>> str(mydata)
>>> (mydata)
>>>
>>> ### Doing the following within each level of the factor "mydata$group":
>>> ### Create a new variable ("new.value") that equals:
>>> ### myvalue in the same week * 0.5 +
>>> ### myvalue 1 week ago * 0.35
>>> ### myvalue 2 weeks ago * 0.15
>>>
>>> groups<-levels(mydata$group)
>>> (groups)
>>>
>>> mydata[["new.value"]]<-mydata[["myvalue"]]*0.5
>>>
>>> for(i in groups){ # looping through groups
>>> temp.data<-mydata[mydata$group %in% i,] # selecting values for one group
>>> temp.data[2,"new.value"]<-temp.data[["new.value"]][2]+temp.data[1,"myvalue"]*0.35
>>> # 2nd new value
>>> for(myrow in 3:nrow(temp.data)){ # Starting in row 3 and looping through
>>> rows
>>>
>>> temp.data[myrow,"new.value"]<-temp.data[["new.value"]][myrow]+temp.data[(myrow-1),"myvalue"]*.35+temp.data[(myrow-2),"myvalue"]*.15
>>> }
>>> mydata[mydata$group %in% i,]<-temp.data
>>> }
>>>
>>>
>>> --
>>> Dimitri Liakhovitski
>>> Ninah Consulting
>>> www.ninah.com
>>>
>>> ______________________________________________
>>> R-help@r-project.org 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.
>>>
>>
>
>
>
> --
> Dimitri Liakhovitski
> Ninah Consulting
> www.ninah.com
>
______________________________________________
R-help@r-project.org 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.
