Displaying 20 results from an estimated 800 matches similar to: "glm.nb and anova"
2002 Jan 02
0
comparative rendering of modeling outputs
This note is to r-devel rather than r-announce because it
notes an experimental package that addresses issues that
intersect with broader developmental issues in R.
I have posted the package
cremo = Comparative REndering of Modeling Outputs
for retrival at
http://www.biostat.harvard.edu/~carey/cremo.html
This package addresses the problem of assembling and
rendering results of multiple
2015 Nov 21
0
[Aarch64 v2 08/18] Add Neon fixed-point implementation of xcorr_kernel.
Used for celt_pitch_xcorr on aarch64, and celt_fir and celt_iir on both armv7 and aarch64.
---
celt/arm/arm_celt_map.c | 17 +++++++++++++
celt/arm/celt_neon_intr.c | 61 ++++++++++++++++++++++++++++++++++++++++++++++-
celt/arm/pitch_arm.h | 31 +++++++++++++++++++++++-
3 files changed, 107 insertions(+), 2 deletions(-)
diff --git a/celt/arm/arm_celt_map.c b/celt/arm/arm_celt_map.c
index
2011 Aug 15
1
update() ignores object
Hi all,
I'm extracting the name of the term in a regression model that
dropterm specifies as the least significant one, and I'm assigning
this name to an object. However, when I use update(), it ignores this
object. Is there a way I can make it not ignore it? A reproducible
example is below:
> lm(x1~1+y1*y2+y3+y4,data=anscombe)->my.lm
>
2011 Mar 31
1
rank of Matrix
Dear list,
Can anyone tell me how to obtain the rank of a sparse Matrix, for
example from package Matrix (class dgCMatrix)? Here is an example of
QR decomposition of a sparse matrix (from the sparseQR class help).
library(Matrix)
data(KNex)
mm <- KNex$mm
str(mmQR <- qr(mm))
Similarly, using the functions/classes from the relatively new
MatrixModels package:
library(MatrixModels)
2008 Aug 13
1
summary.manova rank deficiency error + data
Dear R-users;
Previously I posted a question about the problem of rank deficiency in
summary.manova. As somebody suggested, I'm attaching a small part of
the data set.
#***************************************************
"test" <-
structure(.Data = list(structure(.Data = c(rep(1,3),rep(2,18),rep(3,10)),
levels = c("1", "2", "3"),
class =
2016 Apr 30
4
Removing NAs from dataframe (for use in Vioplot)
Hi
First post and a relative R newbie....
I am using the vioplot library to produce some violin plots. I have an input CSV with columns off irregular length that contain NAs. I want to strip the NAs out and produce a multiple violin plot automatically labelled using the headers. At the moment I do this
Code:?
ds1 = read.csv("http://www.lecturematerials.co.uk/data/spelling.csv")
2010 Feb 28
4
Reducing a matrix
I wish to rearrange the matrix, df, such that all there are not repeated x values. Particularly, for each value of x that is reated, the corresponded y value should fall under the appropriate column. For example, the x value 3 appears 4 times under the different columns of y, i.e. y1,y2,y3,y4. The output should be such that for the lone value of 3 selected for x, the corresponding row entries
2011 Dec 19
1
Training parameters for a HMM
Hi,
I'm a newbie to the world of HMMs and HMMs in R. I've had a look at
the hmm package and the RHmm package but I couldn't see anything
straightforward on how a labelled sequential dataset with observed
values and underlying states might be used to construct and train a
HMM based on that data and no pre-computed values for the transition,
emission or initial state distributions. Does
2008 Dec 29
4
Merge or combine data frames with missing columns
Hi R-experts,
suppose I have a list with containing data frame elements:
[[1]]
(Intercept) y1 y2 y3 y4
-6.64 0.761 0.383 0.775 0.163
[[2]]
(Intercept) y2 y3
-3.858 0.854 0.834
Now I want to put them into ONE dataframe like this:
(Intercept) y1
1998 Nov 09
2
no subject (file transmission)
RNG in R and Splus 3.4
Prof. Ripley asked the details of the example.
We were doing parametric bootstrap, so it is similar to simulation.
Anyway here is the details.
We start with a sample of 19 positive numbers. We know the sample
is from truncated exp(0.3)...only the truncation point, theta, is unknown.
In other words, the sample can be generated from something like
x1 <- rexp(100,
1998 Nov 09
2
no subject (file transmission)
RNG in R and Splus 3.4
Prof. Ripley asked the details of the example.
We were doing parametric bootstrap, so it is similar to simulation.
Anyway here is the details.
We start with a sample of 19 positive numbers. We know the sample
is from truncated exp(0.3)...only the truncation point, theta, is unknown.
In other words, the sample can be generated from something like
x1 <- rexp(100,
2006 Aug 29
2
lattice/xyplot: plotting 4 variables in two panels - can this be done?
Hi,
I would like to create a plot of y1,y2,y3,y4 against x for several subjects such that y1 and y2 are plotted against x in one panel and y3 and y4 against x in another panel. Thus if there are 3 subjects I should end up with 6 panels. Is there a simple way of doing so (i.e. without calling xyplot() several times, and then padding the results together)??
Regards
S?ren
[R-pkgs] New package: `lavaan' for latent variable analysis (including structural equation modeling)
2010 May 24
2
[R-pkgs] New package: `lavaan' for latent variable analysis (including structural equation modeling)
Hi Yves
lavaan looks like a very nice package. From the tutorial introduction
I see you create path diagrams for some of the models you describe.
How did you do this? I don't see a function for this in the package.
I know there is a path.diagram function in the sem package that uses
dot to draw the diagram, but I've always found the layouts from dot
somewhat strange for path diagrams
2011 Apr 27
0
lavaan version 0.4-8
Dear R-users,
A new version of `lavaan' (for latent variable analysis) is now
available on CRAN. The current version of lavaan (0.4-8) can be used for
path analysis, confirmatory factor analysis, structural equation
modeling, and growth curve modeling.
More information can be found on the website: http://lavaan.org
To get a first impression of how the 'lavaan model syntax' looks
2011 Apr 27
0
lavaan version 0.4-8
Dear R-users,
A new version of `lavaan' (for latent variable analysis) is now
available on CRAN. The current version of lavaan (0.4-8) can be used for
path analysis, confirmatory factor analysis, structural equation
modeling, and growth curve modeling.
More information can be found on the website: http://lavaan.org
To get a first impression of how the 'lavaan model syntax' looks
2010 May 19
0
New package: `lavaan' for latent variable analysis (including structural equation modeling)
Dear R-users,
A new package called `lavaan' (for latent variable analysis) has been
uploaded to CRAN. The current version of lavaan (0.3-1) can be used for
path analysis, confirmatory factor analysis, structural equation
modeling, and growth curve modeling.
More information can be found on the website: http://lavaan.org
Some notable features of lavaan:
- the 'lavaan model
2010 May 19
0
New package: `lavaan' for latent variable analysis (including structural equation modeling)
Dear R-users,
A new package called `lavaan' (for latent variable analysis) has been
uploaded to CRAN. The current version of lavaan (0.3-1) can be used for
path analysis, confirmatory factor analysis, structural equation
modeling, and growth curve modeling.
More information can be found on the website: http://lavaan.org
Some notable features of lavaan:
- the 'lavaan model
2011 Jun 23
0
Loops, Paste, Apply? What is the best way to set up a list of many equations?
Is there a way to apply paste to?list(form1 = EQ1, form2 = EQ2, form3 = EQ3, form4 = EQ4)?such that I don't have to write form1=EQ1 for all my models?(I might have a list of 20 or more)? I also need the EQs to read the formulas associated with them.
For example, below, I was able to automate the name assignment but I could not figure out how to?to set up the list using?paste or other
2002 Apr 30
1
MemoryProblem in R-1.4.1
Hi all,
In a simulation context, I'm applying some my function, "myfun" say, to a
list of glm obj, "list.glm":
>length(list.glm) #number of samples simulated
[1] 1000
>class(list.glm[[324]]) #any component of the list
[1] "glm" "lm"
>length(list.glm[[290]]$y) #sample size
[1] 1000
Because length(list.glm) and the sample size are rather large,
2005 Nov 08
1
Interpretation of output from glm
I am fitting a logistic model to binary data. The response variable is a
factor (0 or 1) and all predictors are continuous variables. The main
predictor is LT (I expect a logistic relation between LT and the
probability of being mature) and the other are variables I expect to modify
this relation.
I want to test if all predictors contribute significantly for the fit or not
I fit the full