number to volume weighted distribution

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number to volume weighted distribution

PIKAL Petr
Dear all

Strictly speaking it is not R question but as you are the most capable persons I know I give it a try.

I am strugling with recalculation of number weighted to volume weighted distribution.

Suppose I have objects (cubes) with size

x<- c(rep(10,20), rep(100, 10), rep(300,5))
I can get

plot(ecdf(x))

or the number weighted average

mean(x)
[1] 77.14286

or volume weighted average
weighted.mean(x, (x/sum(x^3)))
[1] 204.4444

However I am struggling with volume weighted ecdf.

Can you please give me some hints?

Cheers
Petr


________________________________
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Re: number to volume weighted distribution

Duncan Murdoch-2
On 24/11/2017 6:27 AM, PIKAL Petr wrote:

> Dear all
>
> Strictly speaking it is not R question but as you are the most capable persons I know I give it a try.
>
> I am strugling with recalculation of number weighted to volume weighted distribution.
>
> Suppose I have objects (cubes) with size
>
> x<- c(rep(10,20), rep(100, 10), rep(300,5))
> I can get
>
> plot(ecdf(x))
>
> or the number weighted average
>
> mean(x)
> [1] 77.14286
>
> or volume weighted average
> weighted.mean(x, (x/sum(x^3)))
> [1] 204.4444
>
> However I am struggling with volume weighted ecdf.
>
> Can you please give me some hints?

I believe base R doesn't have a function for this, but Google says it
exists in a couple of packages:  spatstat, Hmisc.  But you seem to be
asking about a definition rather than a function:  it is obtained simply
by normalizing the weights to sum to 1, then evaluating cumulative sums
of them.

Duncan Murdoch

______________________________________________
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Re: number to volume weighted distribution

PIKAL Petr
Hi Duncan

I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably).
Ecdf(x, q=.5)
Ecdf(x, weights=xw,col=2, add=T, q=.5)
wtd.quantile(x)
  0%  25%  50%  75% 100%
  10   10   10  100  300
wtd.quantile(x, weights=xw, type="i/n")
      0%      25%      50%      75%     100%
 10.0000 138.8667 192.5778 246.2889 300.0000

But could you please be more specific in this?

> But you seem to be asking about a
> definition rather than a function:  it is obtained simply by normalizing the
> weights to sum to 1, then evaluating cumulative sums of them.

Actually, when I correctly calculate weights

xw <- (x^3)/sum(x^3)
sum(xw) equals to 1

but how can I plot ecdf with volume weighted data. Obviously

ecdf(x*xw) or ecdf(x^3*xw) is not correct.

Cheers
Petr

> -----Original Message-----
> From: Duncan Murdoch [mailto:[hidden email]]
> Sent: Friday, November 24, 2017 12:36 PM
> To: PIKAL Petr <[hidden email]>; [hidden email]
> Subject: Re: [R] number to volume weighted distribution
>
> On 24/11/2017 6:27 AM, PIKAL Petr wrote:
> > Dear all
> >
> > Strictly speaking it is not R question but as you are the most capable persons I
> know I give it a try.
> >
> > I am strugling with recalculation of number weighted to volume weighted
> distribution.
> >
> > Suppose I have objects (cubes) with size
> >
> > x<- c(rep(10,20), rep(100, 10), rep(300,5)) I can get
> >
> > plot(ecdf(x))
> >
> > or the number weighted average
> >
> > mean(x)
> > [1] 77.14286
> >
> > or volume weighted average
> > weighted.mean(x, (x/sum(x^3)))
> > [1] 204.4444
> >
> > However I am struggling with volume weighted ecdf.
> >
> > Can you please give me some hints?
>
> I believe base R doesn't have a function for this, but Google says it exists in a
> couple of packages:  spatstat, Hmisc.  But you seem to be asking about a
> definition rather than a function:  it is obtained simply by normalizing the
> weights to sum to 1, then evaluating cumulative sums of them.
>
> Duncan Murdoch

________________________________
Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny pouze jeho adresátům.
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V případě, že je tento e-mail součástí obchodního jednání:
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- trvá odesílatel na tom, že příslušná smlouva je uzavřena teprve výslovným dosažením shody na všech jejích náležitostech.
- odesílatel tohoto emailu informuje, že není oprávněn uzavírat za společnost žádné smlouvy s výjimkou případů, kdy k tomu byl písemně zmocněn nebo písemně pověřen a takové pověření nebo plná moc byly adresátovi tohoto emailu případně osobě, kterou adresát zastupuje, předloženy nebo jejich existence je adresátovi či osobě jím zastoupené známá.

This e-mail and any documents attached to it may be confidential and are intended only for its intended recipients.
If you received this e-mail by mistake, please immediately inform its sender. Delete the contents of this e-mail with all attachments and its copies from your system.
If you are not the intended recipient of this e-mail, you are not authorized to use, disseminate, copy or disclose this e-mail in any manner.
The sender of this e-mail shall not be liable for any possible damage caused by modifications of the e-mail or by delay with transfer of the email.

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- the sender reserves the right to end negotiations about entering into a contract in any time, for any reason, and without stating any reasoning.
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- the sender of this e-mail informs that he/she is not authorized to enter into any contracts on behalf of the company except for cases in which he/she is expressly authorized to do so in writing, and such authorization or power of attorney is submitted to the recipient or the person represented by the recipient, or the existence of such authorization is known to the recipient of the person represented by the recipient.
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Re: number to volume weighted distribution

Thierry Onkelinx
Hi Petr,

I think that Duncan suggests something like this:

x<- c(rep(10,20), rep(300,5), rep(100, 10))
tx <- table(x)

prop.x <- tx / sum(tx)
vx <- as.integer(names(tx))
prop.wx <- tx * vx / sum(tx * vx)

plot(ecdf(x))
plot(vx, cumsum(prop.x), ylim = 0:1)
plot(vx, cumsum(prop.wx), ylim = 0:1)

Best regards,

Thierry

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
[hidden email]
Kliniekstraat 25, B-1070 Brussel
www.inbo.be

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2017-11-24 14:30 GMT+01:00 PIKAL Petr <[hidden email]>:

> Hi Duncan
>
> I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably).
> Ecdf(x, q=.5)
> Ecdf(x, weights=xw,col=2, add=T, q=.5)
> wtd.quantile(x)
>   0%  25%  50%  75% 100%
>   10   10   10  100  300
> wtd.quantile(x, weights=xw, type="i/n")
>       0%      25%      50%      75%     100%
>  10.0000 138.8667 192.5778 246.2889 300.0000
>
> But could you please be more specific in this?
>
>> But you seem to be asking about a
>> definition rather than a function:  it is obtained simply by normalizing the
>> weights to sum to 1, then evaluating cumulative sums of them.
>
> Actually, when I correctly calculate weights
>
> xw <- (x^3)/sum(x^3)
> sum(xw) equals to 1
>
> but how can I plot ecdf with volume weighted data. Obviously
>
> ecdf(x*xw) or ecdf(x^3*xw) is not correct.
>
> Cheers
> Petr
>
>> -----Original Message-----
>> From: Duncan Murdoch [mailto:[hidden email]]
>> Sent: Friday, November 24, 2017 12:36 PM
>> To: PIKAL Petr <[hidden email]>; [hidden email]
>> Subject: Re: [R] number to volume weighted distribution
>>
>> On 24/11/2017 6:27 AM, PIKAL Petr wrote:
>> > Dear all
>> >
>> > Strictly speaking it is not R question but as you are the most capable persons I
>> know I give it a try.
>> >
>> > I am strugling with recalculation of number weighted to volume weighted
>> distribution.
>> >
>> > Suppose I have objects (cubes) with size
>> >
>> > x<- c(rep(10,20), rep(100, 10), rep(300,5)) I can get
>> >
>> > plot(ecdf(x))
>> >
>> > or the number weighted average
>> >
>> > mean(x)
>> > [1] 77.14286
>> >
>> > or volume weighted average
>> > weighted.mean(x, (x/sum(x^3)))
>> > [1] 204.4444
>> >
>> > However I am struggling with volume weighted ecdf.
>> >
>> > Can you please give me some hints?
>>
>> I believe base R doesn't have a function for this, but Google says it exists in a
>> couple of packages:  spatstat, Hmisc.  But you seem to be asking about a
>> definition rather than a function:  it is obtained simply by normalizing the
>> weights to sum to 1, then evaluating cumulative sums of them.
>>
>> Duncan Murdoch
>
> ________________________________
> Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny pouze jeho adresátům.
> Jestliže jste obdržel(a) tento e-mail omylem, informujte laskavě neprodleně jeho odesílatele. Obsah tohoto emailu i s přílohami a jeho kopie vymažte ze svého systému.
> Nejste-li zamýšleným adresátem tohoto emailu, nejste oprávněni tento email jakkoliv užívat, rozšiřovat, kopírovat či zveřejňovat.
> Odesílatel e-mailu neodpovídá za eventuální škodu způsobenou modifikacemi či zpožděním přenosu e-mailu.
>
> V případě, že je tento e-mail součástí obchodního jednání:
> - vyhrazuje si odesílatel právo ukončit kdykoliv jednání o uzavření smlouvy, a to z jakéhokoliv důvodu i bez uvedení důvodu.
> - a obsahuje-li nabídku, je adresát oprávněn nabídku bezodkladně přijmout; Odesílatel tohoto e-mailu (nabídky) vylučuje přijetí nabídky ze strany příjemce s dodatkem či odchylkou.
> - trvá odesílatel na tom, že příslušná smlouva je uzavřena teprve výslovným dosažením shody na všech jejích náležitostech.
> - odesílatel tohoto emailu informuje, že není oprávněn uzavírat za společnost žádné smlouvy s výjimkou případů, kdy k tomu byl písemně zmocněn nebo písemně pověřen a takové pověření nebo plná moc byly adresátovi tohoto emailu případně osobě, kterou adresát zastupuje, předloženy nebo jejich existence je adresátovi či osobě jím zastoupené známá.
>
> This e-mail and any documents attached to it may be confidential and are intended only for its intended recipients.
> If you received this e-mail by mistake, please immediately inform its sender. Delete the contents of this e-mail with all attachments and its copies from your system.
> If you are not the intended recipient of this e-mail, you are not authorized to use, disseminate, copy or disclose this e-mail in any manner.
> The sender of this e-mail shall not be liable for any possible damage caused by modifications of the e-mail or by delay with transfer of the email.
>
> In case that this e-mail forms part of business dealings:
> - the sender reserves the right to end negotiations about entering into a contract in any time, for any reason, and without stating any reasoning.
> - if the e-mail contains an offer, the recipient is entitled to immediately accept such offer; The sender of this e-mail (offer) excludes any acceptance of the offer on the part of the recipient containing any amendment or variation.
> - the sender insists on that the respective contract is concluded only upon an express mutual agreement on all its aspects.
> - the sender of this e-mail informs that he/she is not authorized to enter into any contracts on behalf of the company except for cases in which he/she is expressly authorized to do so in writing, and such authorization or power of attorney is submitted to the recipient or the person represented by the recipient, or the existence of such authorization is known to the recipient of the person represented by the recipient.
> ______________________________________________
> [hidden email] 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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Re: number to volume weighted distribution

PIKAL Petr
Hi Thierry

Thanks for clarifiyng. I spoke about using ecdf because it gives me possibility to calculate proportion of objects below some threshold (quantiles) quite easily.

quantInv <- function(distr, value) ecdf(distr)(value)

> quantInv(x,80)*100
[1] 57.14286

I believe that such value could be calculated from this cumsum construction too. However with real data (hundereds of "x" values), Ecdf and wtd.quantile works quite good so I can live without it (I do not want to reinvent wheel).

Thanks again.
Cheers
Petr


> -----Original Message-----
> From: Thierry Onkelinx [mailto:[hidden email]]
> Sent: Friday, November 24, 2017 10:02 PM
> To: PIKAL Petr <[hidden email]>
> Cc: Duncan Murdoch <[hidden email]>; [hidden email]
> Subject: Re: [R] number to volume weighted distribution
>
> Hi Petr,
>
> I think that Duncan suggests something like this:
>
> x<- c(rep(10,20), rep(300,5), rep(100, 10)) tx <- table(x)
>
> prop.x <- tx / sum(tx)
> vx <- as.integer(names(tx))
> prop.wx <- tx * vx / sum(tx * vx)
>
> plot(ecdf(x))
> plot(vx, cumsum(prop.x), ylim = 0:1)
> plot(vx, cumsum(prop.wx), ylim = 0:1)
>
> Best regards,
>
> Thierry
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN
> BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team
> Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> [hidden email] Kliniekstraat 25, B-1070 Brussel www.inbo.be
>
>
>
>
> 2017-11-24 14:30 GMT+01:00 PIKAL Petr <[hidden email]>:
> > Hi Duncan
> >
> > I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably).
> > Ecdf(x, q=.5)
> > Ecdf(x, weights=xw,col=2, add=T, q=.5)
> > wtd.quantile(x)
> >   0%  25%  50%  75% 100%
> >   10   10   10  100  300
> > wtd.quantile(x, weights=xw, type="i/n")
> >       0%      25%      50%      75%     100%
> >  10.0000 138.8667 192.5778 246.2889 300.0000
> >
> > But could you please be more specific in this?
> >
> >> But you seem to be asking about a
> >> definition rather than a function:  it is obtained simply by
> >> normalizing the weights to sum to 1, then evaluating cumulative sums of
> them.
> >
> > Actually, when I correctly calculate weights
> >
> > xw <- (x^3)/sum(x^3)
> > sum(xw) equals to 1
> >
> > but how can I plot ecdf with volume weighted data. Obviously
> >
> > ecdf(x*xw) or ecdf(x^3*xw) is not correct.
> >
> > Cheers
> > Petr
> >
> >> -----Original Message-----
> >> From: Duncan Murdoch [mailto:[hidden email]]
> >> Sent: Friday, November 24, 2017 12:36 PM
> >> To: PIKAL Petr <[hidden email]>; [hidden email]
> >> Subject: Re: [R] number to volume weighted distribution
> >>
> >> On 24/11/2017 6:27 AM, PIKAL Petr wrote:
> >> > Dear all
> >> >
> >> > Strictly speaking it is not R question but as you are the most
> >> > capable persons I
> >> know I give it a try.
> >> >
> >> > I am strugling with recalculation of number weighted to volume
> >> > weighted
> >> distribution.
> >> >
> >> > Suppose I have objects (cubes) with size
> >> >
> >> > x<- c(rep(10,20), rep(100, 10), rep(300,5)) I can get
> >> >
> >> > plot(ecdf(x))
> >> >
> >> > or the number weighted average
> >> >
> >> > mean(x)
> >> > [1] 77.14286
> >> >
> >> > or volume weighted average
> >> > weighted.mean(x, (x/sum(x^3)))
> >> > [1] 204.4444
> >> >
> >> > However I am struggling with volume weighted ecdf.
> >> >
> >> > Can you please give me some hints?
> >>
> >> I believe base R doesn't have a function for this, but Google says it
> >> exists in a couple of packages:  spatstat, Hmisc.  But you seem to be
> >> asking about a definition rather than a function:  it is obtained
> >> simply by normalizing the weights to sum to 1, then evaluating cumulative
> sums of them.
> >>
> >> Duncan Murdoch
> >

________________________________
Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny pouze jeho adresátům.
Jestliže jste obdržel(a) tento e-mail omylem, informujte laskavě neprodleně jeho odesílatele. Obsah tohoto emailu i s přílohami a jeho kopie vymažte ze svého systému.
Nejste-li zamýšleným adresátem tohoto emailu, nejste oprávněni tento email jakkoliv užívat, rozšiřovat, kopírovat či zveřejňovat.
Odesílatel e-mailu neodpovídá za eventuální škodu způsobenou modifikacemi či zpožděním přenosu e-mailu.

V případě, že je tento e-mail součástí obchodního jednání:
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