Hi Paul,
Have you seen this site?
http://blog.oraylis.de/2010/05/german-map-spatial-data-for-plz-postal-code-regions/
This seems to have the solution you want, and perhaps some useful
stuff about aggregating postal zones. For one off maps, I usually just
look at par("usr") to get the current plot
Hi Michael,
If you want to hardwire the title line, this may help. Very hacky, but...
print.scree.ca<-function(x,digits=5,...) {
cat("Singular values and Principal inertias (eigenvalues)\n\n")
cat(formatC(
c("Singular","Principal","Percent","Cumulative","Scree plot"),
width=10),"\n")
cat(fo
Ask on the BioConductor list, not here.
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll
On Fri, Feb 6, 2015 at 9:27 PM, Beverly Nguyen wrote:
> I am working on a pr
I am working on a project, and have been given a list of instructions as to
how to analyze microarray data. I am to use the affy and affyPLM packages
from Bioconductor.
I used ReadAffy() to read in my CEL files, then called rma() to normalize
the data. I now that this function returns an Expressio
I am new to the R Kohonen package. I plotted the counts per cell and then
compared it to the unit.classif. from the som output - but I can't seem to
get it to match up. Cells that show no counts in the counts plot have 3 or
more data objects assigned to them in the unit. classif. I can provide t
Hi Allen,
Thanks for your response. Regarding the issue that Portnoy and PH estimators
may not compute parameters in the tail, I believe this is dependent on the
amount of censoring (e.g., in the extreme case, if all observations are
censored in the upper tail, one cannot obtain estimates in th
Hi,
For your error "object 't1971' not found" can be corrected by subsetting.
t2001 can be done similarly with 2001 replacing 1971.
> t1971 <- data[year==1971,]
> t1971
VOT year Consonant
1 67 1971 k
2 127 1971 k
3 79 1971 k
4 150 1971 k
5 53 1971
Hi,
Forgot to mention that ggplot2 needs to be installed:
> install.packages("ggplot2")
Warning in install.packages :
downloaded length 227 != reported length 227
trying URL
'http://cran.rstudio.com/bin/windows/contrib/3.1/ggplot2_1.0.0.zip'
Content type 'application/zip' length 2675344 bytes
Hi,
Here is my implementation. Modify the data as follows so that it can be
read with read.table and save as "rHelp_20151206.txt" under working
directory.
female male vowel language
391 339 i W.Apache
561 512 e W.Apache
826 670 a W.Apache
453 427 o W.Apache
358 291 i CA.English
454 406 e
Hi,
I am tasked with making a map of German postal codes for a few major cities
in Germany. Each postal code will have a differnt color, depending on a
metric. For simplicity, let's just use population density.
This is what I have achieved so far for London (which I used as an
example). I have be
Hi,
After some thought, I found the treatment of sample mean equal 0 was not
appropriate. I modified the function likelihood.ratio.test.Poisson.
resulting.matrix now has 0.0512 as the average of type I error.
function(lambda, sample.size, significance.level)
{
reject <- 0
sample.mean <- m
In the ca package, the summary method gives the following output, as a
"poor man's scree plot",
showing eigenvalues, their percents, and a character-based scree plot:
# install.packages("ca")
haireye <- margin.table(HairEyeColor, 1:2)
library(ca)
haireye.ca <- ca(haireye)
summary(haireye.ca, ro
> On 06 Feb 2015, at 18:25 , Mohamed Farah wrote:
>
> Peter,
>
> Appreciate the comment. Here is a summary table. Both variables (Profit and
> dividend with 0=yes & 1=no) are binary as pointed out. I have out of 368
> companies of which 342 were profitable and 26 unprofitable. Of the 342, 79
Dear Michael,
Thank you for your comment. My difficulty is concerned with the high
coefficient of the independent variable. The result I get fro running a logit
regression is:
ylog e^x= -3.3499+ X4.4738. Changing the numbers to exponents of e (antilog) to
better interpret the results, I get y
Peter,
Appreciate the comment. Here is a summary table. Both variables (Profit and
dividend with 0=yes & 1=no) are binary as pointed out. I have out of 368
companies of which 342 were profitable and 26 unprofitable. Of the 342, 79 paid
no dividends and 263 paid dividends. Of the 26, 25 paid no
Ashley,
Looking at the code for the crq function it appears that with method="Portnoy"
the tau value is not passed to the fitting function (crq.fit.por) and that
function appears (I didn't delve into the code to make sure of this ...) to
calculate the grid of tau values given the nature of the
The stats package has a mosaicplot function. Perhaps that would help? -- H
On 6 February 2015 at 03:46, meng wrote:
> Hi all:
> If there are two numeric variable:x,y, and I can get paired scatter plot
> by function "pairs".But if x and y are character, and I want to get paired
> mosaic plot,whic
Hi:
You get a gradient for your response variable because it is numeric.
You need to convert it to factor. (Discrete color sets need to be
mapped to discrete variables - a factor is one way to generate a
discrete variable.) Here is one approach to get what you appear to be
looking for.
DF <- dat
I would try one of these illustrations for starts.
interaction2wt (two-way tables) is designed to be used with aov() for testing.
interaction2wt shows all main effects and all two-way interactions for
many factors.
test <-
structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L,
On 06 Feb 2015, at 16:58 , Michael Dewey wrote:
> Dear Mohamed
>
> Your dataset did not make it through, the list strips most attachments.
>
> In my area of application I would be suspicious that such an odds ratio was
> the result of a data error or my misunderstanding of the underlying scie
Dear Mohamed
Your dataset did not make it through, the list strips most attachments.
In my area of application I would be suspicious that such an odds ratio
was the result of a data error or my misunderstanding of the underlying
science. You are probably in the best position to judge both of t
On 06/02/2015 6:46 AM, meng wrote:
Hi all:
If there are two numeric variable:x,y, and I can get paired scatter plot by function
"pairs".But if x and y are character, and I want to get paired mosaic
plot,which function should be used then?
Why not pairs, with a custom panel function? There ar
Hi all:
If there are two numeric variable:x,y, and I can get paired scatter plot by
function "pairs".But if x and y are character, and I want to get paired mosaic
plot,which function should be used then?
Many thanks!
My best.
--
QQ: 1733768559
[[alternative HTML version deleted]
I have run a logit regression with two categorical variables (with 0 and 1) as
the values. i.e. payment (1) / non-payment(0) on profit (profitable =1,
non-profitable=0) on 375 entities. Here is the result from R:
> divgress <-glm(Div~PRFD, family=binomial(link="logit"), data=divs)
> summary(d
Probably the simplest thing there is, but I can't get it to work:
Example for my data:
a <- c(1,1,1,2,2,2,3,3,3)
b <- c(1,2,3,1,2,3,1,2,3)
c <- c(1,2,3,4,5,6,7,8,9)
df <- data.frame(cbind(a,b,c))
I create a heat map with c being the values:
ggplot(df, aes(df$a, df$b, fill = df$c)) +
Hi,
I think that putting all your objects into one single list would be
easier, both to handle it and to save it.
To do it, you can create an empty list with 1000 elements before running
your function and then run your function in a loop (or something
similar) with the output of each run bein
Dear all
I would like to ask for your opinion about possible graphical representation of
such data.
> dput(test)
structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Lab
27 matches
Mail list logo
