Hi
> wrote:
> >Dear Sir,
> >
> >I do appreciate your views. Yes even I was also aware about the non
> >clarity in the question. Actaully, I have a large data having lots of
> >data of low magnitude and few of very high magnitude. In order to
can you explain what is low or high magnitude? Or be
R is a computing tool, and each package has implemented algorithms that have
history and books and papers that allow those algorithms to be used in a
variety if computing environments... from Fortran to Excel to Java to ... R,
and probably beyond.
>From your description I am going to hazard a g
If you have a clear idea what meaning those weights have (?) in the context of
a specific calculation (?), and you know what the weights are (?), then it is
usually trivially easy to do in R. However, your question is vague on all of
those points, so offering you a solution seems like an invita
Dear R Forum
I have a data.frame as
mydat =
c(6,6,5,6,4,6,8,4,6,6,6,3,4,6,5,7,7,4,3,5,5,5,3,6,7,4,4,7,4,3,4,6,4,6,5,4,4,7,6,8,5,6,5,5,8,2,3,5,7,5)
Is there any library or way in R to allocate weights to these values? Actually
I am having a large data, but for illustrative purpose, have consid
Thanks so much. I really appreciate it.
Carlos
On 5/11/2011 3:18 PM, Thomas Lumley-2 [via R] wrote:
> On Thu, May 12, 2011 at 2:43 AM, jour4life <[hidden email]
> > wrote:
> > I have a follow up question. When using svyglm, it does not matter
> that I am
> > not using survey design and only wei
On Thu, May 12, 2011 at 2:43 AM, jour4life wrote:
> I have a follow up question. When using svyglm, it does not matter that I am
> not using survey design and only weights?
> In other words,
>
> fit<-svyglm(y~x1+x2+...xk,data=dataset,weights=weightvariable)
>
> Or am I going to have to construct a
I have a follow up question. When using svyglm, it does not matter that I am
not using survey design and only weights?
In other words,
fit<-svyglm(y~x1+x2+...xk,data=dataset,weights=weightvariable)
Or am I going to have to construct a survey design variable, using only the
weight variable?
Than
On 5/10/2011 3:12 PM, Thomas Lumley-2 [via R] wrote:
> On Tue, May 10, 2011 at 2:50 PM, jour4life <[hidden email]
> > wrote:
>
> > Hello all,
> >
> > I am wondering if there is a way to specify sampling weights for an ols
> > model using sample weights.
> >
> > For instance, right now, my code is:
On Tue, May 10, 2011 at 2:50 PM, jour4life wrote:
> Hello all,
>
> I am wondering if there is a way to specify sampling weights for an ols
> model using sample weights.
>
> For instance, right now, my code is:
>
> fit.ex<-lm(y~x1+x2+x3+...xk,data=dataset,weights=weightvariable.)
> summary(fit.ex)
Hello all,
I am wondering if there is a way to specify sampling weights for an ols
model using sample weights.
For instance, right now, my code is:
fit.ex<-lm(y~x1+x2+x3+...xk,data=dataset,weights=weightvariable.)
summary(fit.ex)
But, there is almost no difference in the coefficients nor standa
Dear expeRts
Is it not the case that very many multi-level datasets have associated
sample weights? But then I don't see a way to include them in the
analyses? Or, how can I make nlme talk to the "survey" package?
Best Wishes
Steve
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R-help@r-project.o
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