> On Feb 1, 2017, at 5:28 AM, CHIRIBOGA Xavier
> wrote:
>
> Dear colleagues,
>
>
> I am trying to perform a GLM. I tried again without using attach()...but
> still is not working.
>
> Do you have any idea to help me?
>
>
> Thank you again,
>
>
> Xavier
>
>
>
> a <- read.table(file.ch
On 01/02/2017 8:28 AM, CHIRIBOGA Xavier wrote:
Dear colleagues,
I am trying to perform a GLM. I tried again without using attach()...but still
is not working.
Do you have any idea to help me?
Thank you again,
Xavier
a <- read.table(file.choose(), h<-T)
The "h<-T" argument doesn't mak
.csv format is still not accepted by the server. When I say it needs to be a
.txt file I mean it it needs to be a .txt file. You need to change its
extension to .txt to prevent your mail client from labeling it as csv which is
a different type even though I, too, would have thought they sh
Thanks. Here is in csv format.
Cheers,
Joaquín.
2015-08-21 12:49 GMT-03:00 Don McKenzie :
> You can save to .csv from OpenOffice.
>
> Sent from my iPad
>
> > On Aug 21, 2015, at 4:45 AM, Joaquín Aldabe
> wrote:
> >
> > Thankyou all by the comments and sorry for not sending in the adequate
> > fo
Thanks for the correction, I learned something new.
Peter
On Fri, Aug 21, 2015 at 7:32 AM, Bert Gunter wrote:
> Inline.
>
> -- Bert
> Bert Gunter
>
> "Data is not information. Information is not knowledge. And knowledge
> is certainly not wisdom."
>-- Clifford Stoll
>
>
> On Thu, Aug 20, 201
Thankyou all by the comments and sorry for not sending in the adequate
format. I don't have the chance to make txt archives as open office doesn't
do it. I'm attaching the data in excel. Please let me know if this is ok.
The graph that is wierd to me is the BBSA vs AMGP. It is supposed that AMGP
h
Inline.
-- Bert
Bert Gunter
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
-- Clifford Stoll
On Thu, Aug 20, 2015 at 10:47 PM, Peter Langfelder
wrote:
> On Thu, Aug 20, 2015 at 10:04 PM, Bert Gunter wrote:
>
>>> I noticed you made two data-f
On Thu, Aug 20, 2015 at 10:04 PM, Bert Gunter wrote:
>> I noticed you made two data-frames, ‘my4s' and ‘my4S'. The `my4S` was built
>> with `cbind` which would create a matrix (probably a character matrix)
>> rather than a data frame.
>
> False. There is a data.frame method for cbind that retur
Inline.
Cheers,
Bert
Bert Gunter
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
-- Clifford Stoll
On Thu, Aug 20, 2015 at 9:06 PM, David Winsemius wrote:
>
>> On Aug 19, 2015, at 8:54 AM, Joaquín Aldabe wrote:
>>
>> Dear All, I´m running a g
> On Aug 19, 2015, at 8:54 AM, Joaquín Aldabe wrote:
>
> Dear All, I´m running a glm with poisson errors and have a doubt when
> ploting the predicted values. One of my variables has a positive slope in
> the summary output, but when I plot the predicted values on the original
> plot it draws a
matthewjones43 kellogg.ox.ac.uk> writes:
>
> Hi, I am not a statistician and so I am sure whatever it is I
> am doing wrong
> must be an obvious error for those who are...Basically I can
> not understand
> why I get NA for variable 'CDSTotal' when running a glm?
> Does anyone have an
> idea o
> On Jul 21, 2015, at 7:30 PM, Rolf Turner wrote:
>
>
> Psigh! Why do people think that it is perfectly OK to undertake statistical
> analyses without knowing or understanding any statistics?
> (I guess it's slightly less dangerous than undertaking to do your own wiring
> without knowing any
Psigh! Why do people think that it is perfectly OK to undertake
statistical analyses without knowing or understanding any statistics?
(I guess it's slightly less dangerous than undertaking to do your own
wiring without knowing anything about being an electrician, but still )
However, to
I think you are looking for
~ Region + Region:Helpers - 1
a.k.a.
~ Region/Helpers - 1
Notice that these are actually the same model as your glm3 (and also as
~Region*Helpers), only the parametrization differs. The latter includes an
overall Helpers term so that the interaction coefficients s
Are you sure your variables are categorical or numeric? Of course, glm
differentiates these two kinds of variables. For example, I ran the
same variable with different modes, the results are very different.
> dat<-data.frame(y=rpois(100,5),xf=as.factor(sample(1:4,100,replace=T)))
> glm(y~xf,data=d
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