On Fri, 22 Sep 2023 10:12:51 +
"Milbert, Sabine (LGL)" wrote:
> Dear R Help Team,
In addition to other misapprehensions that others have pointed out, you
seem to have a fundamental misunderstanding of R-help (and perhaps of
R). There is no such thing as the "R Help Team". This is a *ma
That's embarrassing. Apologies for the garbles HTML posting. I'll see if
this is more readable:
On 9/23/23 05:30, Rui Barradas wrote:
Às 11:12 de 22/09/2023, Milbert, Sabine (LGL) escreveu:
Dear R Help Team,
My research group and I use R scripts for our multivariate data
screening routines.
В Fri, 22 Sep 2023 10:12:51 +
"Milbert, Sabine (LGL)" пишет:
> PS: If this is an issue based on the model training function of the
> caret package and therefore not your responsibility, please let us
> know.
Indeed, as Rui Barradas said, predict() is a generic function. Calling
it with your
On 9/23/23 05:30, Rui Barradas wrote:
> Às 11:12 de 22/09/2023, Milbert, Sabine (LGL) escreveu:
>> Dear R Help Team,
>>
>> My research group and I use R scripts for our multivariate data
>> screening routines. During routine use, we encountered some
>> inconsistencies within the predict() funct
Às 11:12 de 22/09/2023, Milbert, Sabine (LGL) escreveu:
Dear R Help Team,
My research group and I use R scripts for our multivariate data screening
routines. During routine use, we encountered some inconsistencies within the
predict() function of the R Stats Package. Through internal research,
trisgutt hotmail.com> writes:
>
> I am currently using a GLM with Gaussian family to model fish depth~length +
> distance from shore:
>
> model1 <- glm(Depth ~ length + distance from shore,
> family=gaussian(link="log"))
>
> There are no zero depths. I would like to use the above model with t
Maybe this is what you wanted :
Data <- structure(list(y = c(4.5, 4.5, 4.7, 6.7, 6, 4.4, 4.1, 5.3, 4, 4.2, 4.1,
6.4, 5.5, 3.5, 4.6, 4.1, 4.6, 5, 6.2, 5.9, 3.9, 5.3, 6.9, 5.7), lot = c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), duration = c(0
I think you want CI's for intercepts, not "means" (what is a "mean"
for a line??). If so, the ?confint function will give this to you for
the lot effect estimates when applied to a model fitted without an
intercept:
myfit <-lm(y~ lot-1+time)
confint(myfit)
Further discussion should be directed
I recieved this response from the package authors:
This warning comes from the dismo package (predict with Mahanalobis object).
You can ignore it. It will go away with the next version of dismo (you can
get it from R-Forge).
So the problem is in dismo which has not been updated since raster has
Thank you.
Yes I have raised this question with the authors.
--
View this message in context:
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Sent from the R help mailing list archive at Nabble.com.
__
R-help@
Hi,
I am having the same problem. I am running MaxEnt and using the Raster
package.
But when i try to extract the BIL-file from one RasterLayer:
str(pred@file@bandorder), and stack() this BIL-file with other environmental
variables but get the same error..
“In layerNames(x): the layerNames func
On Nov 27, 2012, at 2:33 PM, megmurr wrote:
Hey,
I am having troubles using the 'predict' function with in the Raster
package. I am using pm<-predict(mm, predictors) where mm is the
mahalanobis distance and the predictors are a stack of 6 raster layers
containing environmental variables.
Whe
On Nov 27, 2012, at 2:33 PM, megmurr wrote:
Hey,
I am having troubles using the 'predict' function with in the Raster
package. I am using pm<-predict(mm, predictors) where mm is the
mahalanobis distance and the predictors are a stack of 6 raster layers
containing environmental variables.
Whe
On Sun, Aug 14, 2011 at 7:55 PM, Darius H wrote:
>
>
>
>
>
>
>
>
>
The above whitespace comes about from posting to this list (which
converts emails to plaintext) in HTML. Please set future emails to
plain text (its under text formatting or something like that in
hotmail).
> Hi everyone,
>
> Do
Why not use the x=T and y=T paramemters and see if :
linearmodel=lm(y~x, x=T, y=T)linearmodel$model
(linearmodel$model)
y x
1 2 1
2 4 2
3 6 3
4 8 4
5 10 5
give you useful results. If you want to interpolate or
extrapolate, then search for threads regarding those tasks.
--
David W
On Thu, Jan 22, 2009 at 10:48 PM, Chun Zhang wrote:
> Hi all,
> I am using cross-validation to validate a generalized linear mixed effects
> model fitted using glmmPQL. i found that the predict function has a problem
> and i wonder if anyone has encountered the same problem?
>
> glmm1 = glmmPQL(
The problem comes from fitting the model using a formula like this:
mlogit <- vglm(bcsse$Active ~ bcsse$Impinteg + bcsse$Hsgradyr,
family = multinomial(), na.action=na.pass)
If you write the formula in that form, prediction will be virtually
impossible, because it will be looking for vari
On Sat, Apr 12, 2008 at 1:06 PM, Biago <[EMAIL PROTECTED]> wrote:
>
> Hi all - my first time here and am having an issue with the Predict function.
>
> I am using a tutorial as a guide, locate here:
> http://www.ats.ucla.edu/STAT/R/dae/mlogit.htm
>
> My code gives this error
>
> > newdata1$pre
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