Hello everybody,
I have a problem regarding factor analysis:
As I am using the hetmat()-function from the polycor-package in order to
calculate different kinds of correlation coefficients automatically* I
cannot obtain
factor scores using fit$scores. The problem is that I am using the
Estimados:
Estoy tratando de procesar imagenes de satelites NOAA enviadas en formato
APT (Automatic Picture Transmission). Busque en Internet y encontre un
paquete biOps pero el mismo no esta disponible para la version 3.2.1 que es
la que tengo instalada.
Ustedes conocen otro paquete similar?
Hola chicos,
Les escribo por que tengo la siguiente pregunta. Estoy por descargar unos
mapas y utilizando la función BROWSE abro la página donde se activa la
descarga automáticamente. Pensando en utilizarla para descargar muchos
mapas se me abren muchas paginas, hay alguna función me sirva para
Hi
I am not completely sure what do you want, so here is my guess.
> dat<-structure(list(Measure_id = c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4,
> 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4,
> 5), i = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4,
Es un problema de robustez.
La desviación estandar lo es más bien poco (robusta).
Al introducir ceros en tu muestra (incluso no tantos como en el ejemplo de
Carlos),
la media se deja arrastrar hacia cero y lo valores grandes de tu muestra
aumentan el valor de sd.
No pasaría eso si utilizase una
It is not entirely clear what you are asking for. Can you provide a sample
of the output that you want from the data. Here is the data split by
Measure_id, but not sure what to do with it:
> split(x, x$Measure_id)
$`1`
Measure_id i j value rank
1 1 2 1 1.5 0.750
6
> On Nov 9, 2015, at 9:19 AM, Adams, Jean wrote:
>
> Harun,
>
> Can you give a simple example?
>
> If your cross_section looked like this
> c(144, 179, 214, 39, 284, 109, 74, 4, 249)
> and your other vector looked like this
> c(0, 50, 100, 150, 200, 250, 300, 350)
> what
Do you want the "closest" or what range it is in? If you want the range,
then use 'cut':
> x <- c(144, 179, 214, 39, 284, 109, 74, 4, 249)
> range <- c(0, 50, 100, 150, 200, 250, 300, 350)
> result <- cut(x, breaks = range)
> cbind(x, as.character(result))
x
[1,] "144" "(100,150]"
[2,]
We are preparing an upgrade of the homals package on CRAN. The current
non-packaged version of the code, with theory and examples, is at
http://rpubs.com/deleeuw/87298. The new version implements principal component
analysis, (multiset) canonical correlation analysis, multiple regression
Harun,
Can you give a simple example?
If your cross_section looked like this
c(144, 179, 214, 39, 284, 109, 74, 4, 249)
and your other vector looked like this
c(0, 50, 100, 150, 200, 250, 300, 350)
what would you want your subset to look like?
Jean
On Mon, Nov 9, 2015 at 7:26 AM, Harun Rashid
Dear users,
Thanks for your attention. I’m running a glmm model using the glmmadmb function
provided in the package glmmADMB.
My dependent variable is the number of individuals belonging to a single
species of an aquatic insect, sampled throughout two non-consecutive years. The
samples were
On 09 Nov 2015, at 11:10 , Pascal Oettli via R-help
wrote:
> Martin,
>
> Sorry, but what are you talking about ? Of course I know it is normal
> to get this result. It is what I explained in my message!
And Martin agreed/confirmed. Notice that "you" in English does not
Perdón Albert,
mi explicación era algo fuera de lugar.
No habia abierto el excel y mi ejemplo no se ajustaba en absoluto al tuyo.
Para que el calculo de una varianza tenga sentido hace falta algo de
regularidad.
Tu serie no parece muy estacionaria y me temo que este tipo de medida no sean
en
Hello,
I have a dataset with two columns 1. cross_section (range: 0~635), and
2. elevation. The dataset has more than 100 rows. Now I want to make a
subset on the condition that the 'cross_section' column will pick up the
nearest cell from another vector (say 0, 50,100,150,200,.,650).
How
I've tried others initial solutions and the adjustement was done to power model
in ggplot - geom_smooth.
But, with "nls" I can't do the confidence interval with ggplot - geom_smooth? I
read that with "nls" we have to force "se=FALSE". Is this true?
How can I draw confidence interval in the plot?
Hi users of raster:
When a point lands within a raster cell, the cell is correctly identified.
But when a point lands on the border between two adjacent raster cells,
cell identity seems to be inconsistent. We are wondering if this is an
error?
Example code follows to demonstrate our question:
Dear group,
I have the following data freame
dput(df_all_nodes)
structure(list(Measure_id = c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1,
2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2,
3, 4, 5, 1, 2, 3, 4, 5), i = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 5, 5, 5, 5,
I think you can use predict.psych() in package psych. Since you analyzed a
correlation matrix with fa() it does not have access to the original data.
-
David L Carlson
Department of Anthropology
Texas A University
College Station, TX 77840-4352
Martin,
Sorry, but what are you talking about ? Of course I know it is normal
to get this result. It is what I explained in my message!
Regards,
Pascal
On Mon, Nov 9, 2015 at 6:19 PM, Martin Maechler
wrote:
>> Pascal Oettli via R-help
> Pascal Oettli via R-help
> on Mon, 9 Nov 2015 14:18:37 +0900 writes:
> Dear Tom,
> Running R 3.2.2 on Ubuntu 15.04, if I run dev.list(), I get NULL.
Yes, indeed with all "regular" / "default" versions of R.
I you don't get that, you must have set
HI Dennis and David
Thank you very much! I really appreciate that.
Now I am half way from my final goal. At the end what I would like is the
following output.
New_X1 New_X2 New_X3 Old X1
1 0 0 0_Abbot
2 0 0
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