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Dear list member,
I think that I have detected a strange behavior of the save() command:
> year <- "2000"
> assign(paste0("Var_", year), list(A=10, B=20))
> get(paste0("Var_", year))
$A
[1] 10
$B
[1] 20
# At this point all is ok, I have created a list of name Var_2000
> save(paste0("Var_",
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[[alternative HTML version deleted]]
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R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
Hello,
Though Bert's and David's answers are what you should do, note that some
R functions that need factors will coerce their input variables when
necessary.
Have you tried to run the code you haven't posted without coercing to
factor? It might run...
Hope this helps,
Rui Barradas
On
Or use cut():
> Num <- c(2.2, 2.4, 3.5, 5, 7)
> cut(Num, breaks=c(0,2,4,6), labels=c("Low","Medium","High"))
[1] Medium Medium Medium High
Levels: Low Medium High
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Mon, Apr 9, 2018 at 10:00 AM, Bert Gunter wrote:
>
Hola de nuevo Carlos, he probado a quitar esa variable categórica y me
sigue dando el aviso...
El Lun, 9 de Abril de 2018, 20:17, Carlos J. Gil Bellosta escribió:
> Si, creo que el motivo del warning puede ser ese. Es hipotético, pero
> plausible. Sobre todo cuando tienes más de un 90% de ceros.
En ese caso, ¿tendría sentido el modelo? o ¿debería quitar esa variable
categórica?
Muchas gracias
El Lun, 9 de Abril de 2018, 20:17, Carlos J. Gil Bellosta escribió:
> Si, creo que el motivo del warning puede ser ese. Es hipotético, pero
> plausible. Sobre todo cuando tienes más de un 90% de
Si, creo que el motivo del warning puede ser ese. Es hipotético, pero
plausible. Sobre todo cuando tienes más de un 90% de ceros.
El coeficiente de ese nivel para el modelo de la mixtura (ceros vs binomial
negativa) sería infinito. Y de ahí el warning.
El lun., 9 abr. 2018 a las 20:09,
see also ?cut if this is what you mean.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Apr 9, 2018 at 9:28 AM, Saif Tauheed
Just cast it!
?factor
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Apr 9, 2018 at 9:28 AM, Saif Tauheed wrote:
> Dear Sir,
>
>
¿Quieres decir que para un nivel de una variable categorica todas las
observaciones de la variable respuesta sean ceros?
Gracias
El Lun, 9 de Abril de 2018, 19:59, Carlos J. Gil Bellosta escribió:
> ¿Podría ser que para algún nivel de alguna variable independiente
> categórica solo hubiese
¿Podría ser que para algún nivel de alguna variable independiente
categórica solo hubiese ceros? En ese caso, casi seguro, aparecería ese
tipo de warning.
El lun., 9 abr. 2018 a las 19:00, escribió:
> Muchas gracias por la respuesta. He mirado y los coeficientes no
Try the help files:
?factor
David L Carlson
Department of Anthropology
Texas A University
College Station, TX 77843-4352
-Original Message-
From: R-help On Behalf Of Saif Tauheed
Sent: Monday, April 9, 2018 11:29 AM
Muchas gracias por la respuesta. He mirado y los coeficientes no son altos
pero sí tengo una gran cantidad de ceros en la variable dependiente (más
del 90%). Sin embargo, al incluir otro tipo de variables independientes no
me da ese aviso, dejando la misma variable dependiente.
¿Cómo podría
Dear Sir,
I have xlsx data set which I have imported to R studio. Now some of the
variables are defined as numeric but I want define them as factor variable so
that I run classification algorithm in R.
Please to covert the variables.
Thanks and Regards
Abu Afzal
PhD Eco
JNU
India
Buenas tardes,
Estoy estimando un modelo binomial negativo de ceros inflados (ZINB)
utilizando el comando zeroinfl() del paquete pscl. Al ejecutarlo me da el
siguiente aviso:
Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
¿Sabéis que significa y si puedo usar el modelo aún
Hi!
I am trying to implement the Morris One at a Time (OAT) sensitivity
analysis technique in R using the package 'sensitivity'. The OAT and
similar other techniques in the package requires data frame X (which stores
the design or parameter combinations) to be populated by some function in
the
Your email is hard to read because you sent html email. Please send plain text.
You will need to say what you mean by "join". It's not a standard term with a
universally agreed upon meaning within R.
If you have 5 data frames, each with 5 rows, and it makes sense that after
joining you should
Generally, statistics questions are off topic here, although they do
sometimes intersect R programming issues, as perhaps here.
Nevertheless, I believe your post would fit better on the
r-sig-mixed-models list, where repeated measures and other mixed
effects (/variance components) models are
Dear list,
this seemed to me like a very trivial question, but finally I haven't found
any similar postings with suitable solutions on the net ...
Basically, instead of regressing two simple series of measures 'a' and 'b'
(like b ~ a), I would like to use independent replicate measurements for
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