Displaying 20 results from an estimated 400 matches similar to: "Change title size in plot(model)?"
2007 Sep 25
1
Create grouping from TukeyHSD (as a duncan test does)?
Hello everybody
1. If there is/ever will be a function to perform "duncan multiple range test" please inform me at once.
2. Is there a way to create a grouping as duncan does from TukeyHSD output? My experimental design contained 62 genotypes, so the pairwise comparison is not that usefull and clear to look at. How would I do that? Is there an other test that does give grouping as
2017 Aug 02
3
Remove attribute from netcdf4 object
Dear all
For a model I need to combine several netCDF files into one (which works fine). For better overview I'd like to delete/remove some of the attributes. Is there a simple way doing this?
I'm using the package netcdf4, which creates an object of class(nc) = "ncdf4". It seems that for earlier versions of netcdf objects, there was the function att.delete.nc{RNetCDF}. But
2017 Aug 14
2
ncdf4: Why are NAs converted to _FillValue when saving?
Dear all
I'm a newbie regarding netcdf data. Today I realized that I maybe do not understand some basics of the netcdf. I want to create a *.nc file containing three variables for Switzerland. All data outside of the country are NAs. The third variable is calculated from the first two variables. Basically there is no problem to do that. I copy the file with the data of the first variable,
2017 Aug 14
0
ncdf4: Why are NAs converted to _FillValue when saving?
On Mon, Aug 14, 2017 at 5:29 AM, <raphael.felber at agroscope.admin.ch> wrote:
Dear all
>
> I'm a newbie regarding netcdf data. Today I realized that I maybe do not
> understand some basics of the netcdf. I want to create a *.nc file
> containing three variables for Switzerland. All data outside of the country
> are NAs. The third variable is calculated from the first two
2004 Jun 18
2
Barplots and error indicators: Some R-Code
I' ve seen that several people are looking for a function that creates a
barplot with an error indicators (I was one of them myself). Maybe you will
find the following code helpful (There are some examples how to use it at
the end):
# Creates a barplot.
#bar.plot() needs a datavector for the height of bars and a error
#indicator for the interval
#many of the usual R parameters can be set:
2017 Aug 02
0
Remove attribute from netcdf4 object
Dear Marc
Thanks for your remark. I don't want to use both packages. I mentioned the package RNetCDF to show that there is a similar function I' d like to use.
Raphael
Von: Marc Girondot [mailto:marc.girondot at u-psud.fr]
Gesendet: Mittwoch, 2. August 2017 14:51
An: Felber Raphael Agroscope <raphael.felber at agroscope.admin.ch>; r-help at r-project.org
Betreff: Re: [R] Remove
2017 Sep 07
1
extend limited dimension in netcdf
Dear all
I have to combine 3D netCDF files (lon, lat, time). The files contain data of one month and I need a year file containing all the data. Because the attributes of all files are the same, I copied the first file and appended the data of the other months. This went well until the provider of the data changed the time-dimension from UNLIMITED to LIMITED. Is there a way to change the time
2017 Aug 02
0
Remove attribute from netcdf4 object
Le 02/08/2017 ? 12:03, raphael.felber at agroscope.admin.ch a ?crit :
> Dear all
>
> For a model I need to combine several netCDF files into one (which works fine). For better overview I'd like to delete/remove some of the attributes. Is there a simple way doing this?
>
> I'm using the package netcdf4, which creates an object of class(nc) = "ncdf4". It seems that
2007 Aug 22
4
within-subject factors in lme
I don't think, this has been answered:
> I'm trying to run a 3-way within-subject anova in lme with 3
> fixed factors (Trust, Sex, and Freq), but get stuck with handling
> the random effects. As I want to include all the possible random
> effects in the model, it would be something more or less
> equivalent to using aov
>
> > fit.aov <- aov(Beta ~
>
2017 Aug 02
0
Remove attribute from netcdf4 object
Hi Marc
That's a workaround I can use. Thanks. I'm a newbie regarding netCDF data. Is there any information I'm losing when switching between the packages?
Raphael
Von: Marc Girondot [mailto:marc.girondot at u-psud.fr]
Gesendet: Mittwoch, 2. August 2017 15:13
An: Felber Raphael Agroscope <raphael.felber at agroscope.admin.ch>
Betreff: Re: AW: [R] Remove attribute from netcdf4
2007 Mar 08
2
Using logarithmic y-axis (density) in a histogram
Hi,
I am searching for a possibility to display a logarithimic y-axis in a histogram. With plot that's easy (e.g.
plot(1:10, log="y")
but for histograms this does not work the same way: I tried
hist(rnorm(1000), freq=FALSE, seq(-4, 4, .5), ylim=c(0.001, 0.5), log="y")
Which gives the expected histogram but also warnings for my log="y" command
2017 Aug 22
4
How to benchmark speed of load/readRDS correctly
Dear all
I was thinking about efficient reading data into R and tried several ways to test if load(file.Rdata) or readRDS(file.rds) is faster. The files file.Rdata and file.rds contain the same data, the first created with save(d, ' file.Rdata', compress=F) and the second with saveRDS(d, ' file.rds', compress=F).
First I used the function microbenchmark() and was a astonished
2017 Aug 22
0
How to benchmark speed of load/readRDS correctly
The large value for maximum time may be due to garbage collection, which
happens periodically. E.g., try the following, where the
unlist(as.list()) creates a lot of garbage. I get a very large time every
102 or 51 iterations and a moderately large time more often
mb <- microbenchmark::microbenchmark({ x <- as.list(sin(1:5e5)); x <-
unlist(x) / cos(1:5e5) ; sum(x) }, times=1000)
2017 Aug 22
1
How to benchmark speed of load/readRDS correctly
Note that if you force a garbage collection each iteration the times are
more stable. However, on the average it is faster to let the garbage
collector decide when to leap into action.
mb_gc <- microbenchmark::microbenchmark(gc(), { x <- as.list(sin(1:5e5)); x
<- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000,
control=list(order="inorder"))
with(mb_gc,
2017 Sep 18
1
Data arrangement for PLSDA using the ropls package
Hello,
I would like to do a partial least square discriminant analysis (PLSDA) in R using the package "ropls"
Which is in R available via the R command :
source("https://bioconductor.org/biocLite.R")
I try to do a PLSDA to illustrate the impact of two genders (AP,C) on 5 compounds measured in persons (samples) should be illustrated. When I try to do a PLSDA I get the warning
2008 Jan 29
1
Guidance for reporting results from lme test?
En innebygd og tegnsett-uspesifisert tekst ble skilt ut...
Navn: ikke tilgjengelig
Nettadresse: https://stat.ethz.ch/pipermail/r-help/attachments/20080129/5f8a6ac4/attachment.pl
2007 Aug 07
2
GLMM: MEEM error due to dichotomous variables
I am trying to run a GLMM on some binomial data. My fixed factors include 2
dichotomous variables, day, and distance. When I run the model:
modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial")
I get the error:
iteration 1
Error in MEEM(object, conLin, control$niterEM) :
Singularity in backsolve at level 0, block 1
>From looking at previous help
2007 Jun 04
3
Why is the R mailing list so hard to figure out?
Why does the R mailing list need such an unusual and customized user interface?
Last January, I figured out how to read Usenet mailing lists ( or
Usenet groups ) and they all pretty much work the same, learn to use
one, you've learned to use them all ( gnu.misc.discuss ,
comp.lang.lisp , and so on ).
What's the best way to view and read discussions in this group for
recent days? Can I
2007 Jan 16
1
nested hierarchical design
Dear R-Helpers,
I would like to know what syntax I need to use to do a nested anova for
1. a continuous variable and 2. count data (x out of y)
1. The first I used to do in SPSS and I would like to be able to do it
in R as well.
This is the hierarchical model I would like to use: a continuous
variable explained by factor A(fixed) + factor B(random) nested in A +
factor C (random) nested in
2006 Oct 05
1
lmer BIC changes between output and anova
list,
i am using lmer to fit multilevel models and trying to use anova to compare the models. however, whenever i run the anova, the AIC, BIC and loglik are different from the original model output- as below. can someone help me out with why this is happening? (i'm hoping the output assocaited with the anova is right!).
thank you,
darren
> unconditional<-lmer(log50 ~ 1 + (1 |