R help - Aug 2017 - Zoo rolling window with increasing window size

Hi Joshua, thanks for your prompt reply. However as I said, sum()
function I used here just for demonstrating the problem, I have other
custom function to implement, not necessarily sum()

I am looking for a generic solution for above problem.

Any better idea? Thanks,

On Fri, Aug 11, 2017 at 12:04 AM, Joshua Ulrich <josh.m.ulrich at
gmail.com> wrote:
> Use a `width` of integer index locations.  And you likely want >
"right" (or rollapplyr(), as I used).
>
> R> set.seed(21)
> R> x <- rnorm(10)
> R> rs <- rollapplyr(x, seq_along(x), sum)
> R> cs <- cumsum(x)
> R> identical(rs, cs)
> [1] TRUE
>
>
> On Thu, Aug 10, 2017 at 1:28 PM, Christofer Bogaso
> <bogaso.christofer at gmail.com> wrote:
>> Hi again,
>>
>> I am wondering there is any function for 'zoo' time series,
where I
>> can apply a user defined function rolling window basis, wherein window
>> size is ever increasing i.e. not fixed. For example, let say I have
>> below user defined function and a zoo time series :
>>
>>> library(zoo)
>>
>>> UDF = function(x) sum(x)
>>
>>> TS = zoo(rnorm(10), seq(as.Date('2017-01-01'),
as.Date('2017-01-10'), by = '1 day'))
>>
>>>
>>
>> Now I want to apply UDF (this can be any custom function, however here
>> I put it just quick example) rolling window basis like :
>>
>> 1st data point = 1st data point of TS
>> 2nd data point = sum of 1st and 2nd data points of TS
>> 3rd data point = sum of 1st 2nd and 3rd data points of TS
>>
>> so on
>>
>> I am aware of the rollapply() function from zoo, however, appears like
>> it is only for fixed window size.
>>
>> Appreciate any pointer how to achieve above strategy of implementing
>> rolling calculation based on increased window size.
>>
>> Thanks for your time.
>>
>> ______________________________________________
>> 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.
>
>
>
> --
> Joshua Ulrich  |  about.me/joshuaulrich
> FOSS Trading  |  www.fosstrading.com
> R/Finance 2017 | www.rinfinance.com

Replace "sum" with your custom function's name.  I don't see
any
reason why that wouldn't work, and the problem with my solution is not
clear in your response.

r <- rollapplyr(x, seq_along(x), yourCustomFunctionGoesHere)

On Thu, Aug 10, 2017 at 1:39 PM, Christofer Bogaso
<bogaso.christofer at gmail.com> wrote:
> Hi Joshua, thanks for your prompt reply. However as I said, sum()
> function I used here just for demonstrating the problem, I have other
> custom function to implement, not necessarily sum()
>
> I am looking for a generic solution for above problem.
>
> Any better idea? Thanks,
>
> On Fri, Aug 11, 2017 at 12:04 AM, Joshua Ulrich <josh.m.ulrich at
gmail.com> wrote:
>> Use a `width` of integer index locations.  And you likely want >>
"right" (or rollapplyr(), as I used).
>>
>> R> set.seed(21)
>> R> x <- rnorm(10)
>> R> rs <- rollapplyr(x, seq_along(x), sum)
>> R> cs <- cumsum(x)
>> R> identical(rs, cs)
>> [1] TRUE
>>
>>
>> On Thu, Aug 10, 2017 at 1:28 PM, Christofer Bogaso
>> <bogaso.christofer at gmail.com> wrote:
>>> Hi again,
>>>
>>> I am wondering there is any function for 'zoo' time series,
where I
>>> can apply a user defined function rolling window basis, wherein
window
>>> size is ever increasing i.e. not fixed. For example, let say I have
>>> below user defined function and a zoo time series :
>>>
>>>> library(zoo)
>>>
>>>> UDF = function(x) sum(x)
>>>
>>>> TS = zoo(rnorm(10), seq(as.Date('2017-01-01'),
as.Date('2017-01-10'), by = '1 day'))
>>>
>>>>
>>>
>>> Now I want to apply UDF (this can be any custom function, however
here
>>> I put it just quick example) rolling window basis like :
>>>
>>> 1st data point = 1st data point of TS
>>> 2nd data point = sum of 1st and 2nd data points of TS
>>> 3rd data point = sum of 1st 2nd and 3rd data points of TS
>>>
>>> so on
>>>
>>> I am aware of the rollapply() function from zoo, however, appears
like
>>> it is only for fixed window size.
>>>
>>> Appreciate any pointer how to achieve above strategy of
implementing
>>> rolling calculation based on increased window size.
>>>
>>> Thanks for your time.
>>>
>>> ______________________________________________
>>> 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.
>>
>>
>>
>> --
>> Joshua Ulrich  |  about.me/joshuaulrich
>> FOSS Trading  |  www.fosstrading.com
>> R/Finance 2017 | www.rinfinance.com


-- 
Joshua Ulrich  |  about.me/joshuaulrich
FOSS Trading  |  www.fosstrading.com
R/Finance 2017 | www.rinfinance.com

Something like this?

set.seed(123)
y <- rnorm(20)
sapply(1:length(y),  function(x) sum(y[1:x]))

or this, depending what is the output of your custom function

lapply(1:length(y),  function(x) sum(y[1:x]))

On Thu, Aug 10, 2017 at 8:39 PM, Christofer Bogaso <
bogaso.christofer at gmail.com> wrote:
> Hi Joshua, thanks for your prompt reply. However as I said, sum()
> function I used here just for demonstrating the problem, I have other
> custom function to implement, not necessarily sum()
>
> I am looking for a generic solution for above problem.
>
> Any better idea? Thanks,
>
> On Fri, Aug 11, 2017 at 12:04 AM, Joshua Ulrich <josh.m.ulrich at
gmail.com>
> wrote:
> > Use a `width` of integer index locations.  And you likely want >
> "right" (or rollapplyr(), as I used).
> >
> > R> set.seed(21)
> > R> x <- rnorm(10)
> > R> rs <- rollapplyr(x, seq_along(x), sum)
> > R> cs <- cumsum(x)
> > R> identical(rs, cs)
> > [1] TRUE
> >
> >
> > On Thu, Aug 10, 2017 at 1:28 PM, Christofer Bogaso
> > <bogaso.christofer at gmail.com> wrote:
> >> Hi again,
> >>
> >> I am wondering there is any function for 'zoo' time
series, where I
> >> can apply a user defined function rolling window basis, wherein
window
> >> size is ever increasing i.e. not fixed. For example, let say I
have
> >> below user defined function and a zoo time series :
> >>
> >>> library(zoo)
> >>
> >>> UDF = function(x) sum(x)
> >>
> >>> TS = zoo(rnorm(10), seq(as.Date('2017-01-01'),
as.Date('2017-01-10'),
> by = '1 day'))
> >>
> >>>
> >>
> >> Now I want to apply UDF (this can be any custom function, however
here
> >> I put it just quick example) rolling window basis like :
> >>
> >> 1st data point = 1st data point of TS
> >> 2nd data point = sum of 1st and 2nd data points of TS
> >> 3rd data point = sum of 1st 2nd and 3rd data points of TS
> >>
> >> so on
> >>
> >> I am aware of the rollapply() function from zoo, however, appears
like
> >> it is only for fixed window size.
> >>
> >> Appreciate any pointer how to achieve above strategy of
implementing
> >> rolling calculation based on increased window size.
> >>
> >> Thanks for your time.
> >>
> >> ______________________________________________
> >> 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.
> >
> >
> >
> > --
> > Joshua Ulrich  |  about.me/joshuaulrich
> > FOSS Trading  |  www.fosstrading.com
> > R/Finance 2017 | www.rinfinance.com
>
> ______________________________________________
> 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.
>
	[[alternative HTML version deleted]]

Thanks Joshua, your solution is perfect.

On Fri, Aug 11, 2017 at 12:11 AM, Joshua Ulrich <josh.m.ulrich at
gmail.com> wrote:
> Replace "sum" with your custom function's name.  I don't
see any
> reason why that wouldn't work, and the problem with my solution is not
> clear in your response.
>
> r <- rollapplyr(x, seq_along(x), yourCustomFunctionGoesHere)
>
> On Thu, Aug 10, 2017 at 1:39 PM, Christofer Bogaso
> <bogaso.christofer at gmail.com> wrote:
>> Hi Joshua, thanks for your prompt reply. However as I said, sum()
>> function I used here just for demonstrating the problem, I have other
>> custom function to implement, not necessarily sum()
>>
>> I am looking for a generic solution for above problem.
>>
>> Any better idea? Thanks,
>>
>> On Fri, Aug 11, 2017 at 12:04 AM, Joshua Ulrich <josh.m.ulrich at
gmail.com> wrote:
>>> Use a `width` of integer index locations.  And you likely want
>>> "right" (or rollapplyr(), as I used).
>>>
>>> R> set.seed(21)
>>> R> x <- rnorm(10)
>>> R> rs <- rollapplyr(x, seq_along(x), sum)
>>> R> cs <- cumsum(x)
>>> R> identical(rs, cs)
>>> [1] TRUE
>>>
>>>
>>> On Thu, Aug 10, 2017 at 1:28 PM, Christofer Bogaso
>>> <bogaso.christofer at gmail.com> wrote:
>>>> Hi again,
>>>>
>>>> I am wondering there is any function for 'zoo' time
series, where I
>>>> can apply a user defined function rolling window basis, wherein
window
>>>> size is ever increasing i.e. not fixed. For example, let say I
have
>>>> below user defined function and a zoo time series :
>>>>
>>>>> library(zoo)
>>>>
>>>>> UDF = function(x) sum(x)
>>>>
>>>>> TS = zoo(rnorm(10), seq(as.Date('2017-01-01'),
as.Date('2017-01-10'), by = '1 day'))
>>>>
>>>>>
>>>>
>>>> Now I want to apply UDF (this can be any custom function,
however here
>>>> I put it just quick example) rolling window basis like :
>>>>
>>>> 1st data point = 1st data point of TS
>>>> 2nd data point = sum of 1st and 2nd data points of TS
>>>> 3rd data point = sum of 1st 2nd and 3rd data points of TS
>>>>
>>>> so on
>>>>
>>>> I am aware of the rollapply() function from zoo, however,
appears like
>>>> it is only for fixed window size.
>>>>
>>>> Appreciate any pointer how to achieve above strategy of
implementing
>>>> rolling calculation based on increased window size.
>>>>
>>>> Thanks for your time.
>>>>
>>>> ______________________________________________
>>>> 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.
>>>
>>>
>>>
>>> --
>>> Joshua Ulrich  |  about.me/joshuaulrich
>>> FOSS Trading  |  www.fosstrading.com
>>> R/Finance 2017 | www.rinfinance.com
>
>
>
> --
> Joshua Ulrich  |  about.me/joshuaulrich
> FOSS Trading  |  www.fosstrading.com
> R/Finance 2017 | www.rinfinance.com