res - combn(4,2)
result - LETTERS[res]
dim(result) - dim(res)
result
## Rich
[[alternative HTML version deleted]]
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Jim,
The next step for understanding what happens is to subset a complicated
expression
and see what its sub-pieces are doing.
Since
apply(a[!is.na(a)],2,sum)
doesn't work, start by looking at each of the arguments to apply.
You already verified that
!is.na(a)
gives what you want. Now take
## dadrivr dadr...@gmail.com
## I suggest a lattice plot of all two-way interactions on the
## off-diagonals and all marginal main effects on the main diagonal.
## Please install HH and then ?interaction2wt for some examples.
## install.packages(HH) ## if you don't already have it
library(HH)
On Fri, Mar 5, 2010 at 12:41 PM, Jeff Laake jeff.la...@noaa.gov wrote:
On 3/5/2010 9:19 AM, Frank E Harrell Jr wrote:
You neglected to state your name and affiliation, and your question
demonstrates an allergy to R documentation.
A:B indicates a two-level naming scheme. The naming is
so if I ran an R command that took a
long while to complete, I couldn't switch back to my source buffer and
keep messing around with my code while the R process was doing
whatever it was doing.
Normally Ctrl-G gives control back to you while the R process is still
running.
I would love to see a text oriented towards someone who has never used
anything but Excel, but realizes that to do science today you have to go
beyond the Data analysis toolbar from Excel.
(Plese tell me if you know of any)
Best to all,
Keo.
Please look at *R through Excel, *the book that Erich
Lets take for example an experiment in which I had two between subject
variables - Strain and treatment, and one within - exposure. all the
variables had 2 levels each.
I found an interaction between exposure and Strain and I want to compare
Strain A and B under every exposure (first and
statistics book. I recommend mine
Statistical Analysis and Data Display, An Intermediate Course with
Examples in S-Plus, R, and SAS,
Richard M. Heiberger and Burt Holland, Springer 2004
But I will acknowledge that other books are available.
Rich
__
R
treat_code is a dummy
variable, but that shouldn't matter. Any suggestions?
It does matter to TukeyHSD. If treat_code is a numeric variable with discrete
values 0 and 1, then it does not have class factor. It is true that
aov will give the same
ANOVA table for a two-level factor as for a
Please consider RExcel, which allows complete integration of R and Excel.
See http://rcom.univie.ac.at
for details and examples including a video.
RExcel works in both directions (R to Excel, Excel to R) with
Excel 2010, 2007, 2003, and 2002.
Rich
[[alternative HTML version deleted]]
Frank,
you can collect multiple arguments into a single \item{}
You example simplified becomes
\item{x, y, contrasts}{see \code{\link{glm}}}
Rich
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To overcome the fact that the R installation had
spaces in the path,
The easiest way to deal with spaces is to use the 8.3 names in your paths.
From the DOS CMD window, enter
dir /x
and you will get the 8.3 names. For example
dir /x/ad c:\pr*
cd c:\progra~1\R
dir /x/ad R-2.10.*
Based
## The grouped boxplot is one of the features included in the HH package.
## You will need to install HH if you do not yet have the HH package
## A similar example is posted on my website
##http://astro.ocis.temple.edu/~rmh/HH/bwplot-color.pdf
## This is fake data which I hope mimics the
(2) Suppose I have variable no of datasets 'say n = 10'. I wish to write a
loop assigning each of these datasets to diffrent csv files e.g.
for (i in 1:10)
{
write.csv(data.frame(dataset[,,i]), 'data_set[i].csv', row.names = FALSE)
}
The result of this command is generation of a csv
Please look at the maiz example, the last example in ?MMC
in the HH package, to see how to display pairwiuse contrasts in
split-plot experiments.
Look at the entire example, all the way to the end of the help file.
Rich
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Your results show that you have a rank 2 matrix.
$rank
[1] 2
Therefore the third column of Q for your x is arbitrary.
A better example would be
x - matrix(rnorm(12), 4, 3)
qr(x)
Rich
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This is defined in the help file
?print.trellis
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and provide commented, minimal,
## Artificial data with all interactions significant.
## The interaction2wt plot shows all main effects and all pairwise
## interactions. We see in the Y ~ A|B panel (or in the
## interaction.plot) that Y goes uphill for levels 1 and 2 of B and
## goes down and then up for level 3 of B. This is
## Continuing with the same example, I now show the full set of
contrasts and their
## associated regression coefficients. Remember that regression coefficients in
## models with factors are meaningful only when the dummy variables
are also displayed.
## construct full set of dummy variables to
, shillings, pence), and for unique
indexing of cells in designed experiments.
Rich
## base
## Richard M. Heiberger
## See Section 12.1.4.2 of
## Richard M. Heiberger
## Computation for the Analysis of Designed Experiments
## Wiley, 1989
## defaults to 8 bit binary
base - function(x, basis=c
The dummy variables for the factors in balanced designs are orthogonal.
The treatment dummy variables are not orthogonal to the block dummy variables
for unbalanced designs. That is essentially what the term balanced means.
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Fran,
The trick is to use box.width, not box.ratio.
xyplot(Perc ~ as.POSIXct(hora,format=%d-%m-%Y %H:%M),
data=digrate, groups=Drate, ## key=leg,
xlab=time of the day,
horizontal=FALSE,
scales=list(alternating=FALSE,
tck=c(1,0),
Have you tried dput/dget or dump/source?
On the S-Plus side, you need to tell it to use the older format.
Rich
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SCript with xyplot:
xyplot(Perc~as.POSIXct(hora,format=%d-%m-%Y
%H:%M),digrate,groups=digrate$Drate,key=leg,xlab=time of the day,
scales=list(alternating=F,tck=c(1,0),x=list(at=seq(r[1],r[2],by=hour),labels=format(seq(r[1],r[2],hours),format=%H:%M))),
Continuing from your JUNK example:
xyplot(Creatinine + Estrogen + Ratio ~ Day, data=JUNK, type=l,
outer=TRUE, layout=c(1,3),
scales=list(y=list(relation=free)))
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lapply(1:4, function(i, x, y) {x[i,y[,1]]}, Z, index ) ## reproduces
your results
sapply(1:4, function(i, x, y) {x[i,y[,1]]}, Z, index ) ## collapses
your list into a set of columns
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In addition to Marc's comments, you might want to use
setInternet2()
I am pretty sure this will get you past a firewall to r-project.org.
I think it might also get you access to 127.0.0.1.
Access to 127.0.0.1 is not explicitly mentioned in the help file ?setInternet2
Rich
If you paste
http://127.0.0.1:12300/library/base/html/sum.html
directly into an IE window, will it find it? You need to do that
after the attempt fails
in order to get the right port number for the current instance.
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I have several questions on your goals.
Why are you planning to post-processing outside of R?
Why use CSV files when there are usually better ways to maintain
the structure of the data?
Why do you want to flatten your tables? It looks like a three-dimensional array
would better capture the
The message you are getting is unrelated to reading files. That
probably means you
have loaded a previous work file that is masking something. Type
conflicts(detail=TRUE)
If that doesn't give you the answer, then
try closing R entirely and start a new session from
START Run
m - c(1,4,2,3,7,5)
S - which(m==4)
P - parse(text=S)
R - eval(P)
R
Before you do this, see fortune(106)
fortune(106)
If the answer is parse() you should usually rethink the question.
-- Thomas Lumley
R-help (February 2005)
On Wed, Jan 27, 2010 at 8:59 AM, Joe Trubisz jtrub...@mac.com
## There are at least two options, one using mosaic and the other
using barchart.
## Here are both.
## this is your data
ld-matrix(c(25,25,50,10,30,60,15,35,50,30,30,40),nrow=4,byrow=T)
ntreat2-c(n0,n96,n0,n96)
rownames(ld)-ntreat2
typ-c(gr,fo,le)
colnames(ld)-typ
## now some rearrangements
I don't understand what you are looking for.
The line
barplot(t(ld))
is placing the four treatments side by side, and is also stacking the
three values of typ.
Please indicate what you would like the figure to look like.
Rich
__
You may need to look at some other contrasts than the pairwise.
For example,
3(x.bar_A + x.bar_B) - 2(x.bar_C + x.bar_D + x.bar_E)
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Please look at the aedotplot, in which we plot four variables:
A effect, B effect, relative risk, and CI on the relative risk.
It should be easily modified to plot the odds ratios.
## install.packages(HH) ## if you don't have it yet.
library(aedotplot)
example(aedotplot)
For simple effects in the presence of interaction there are several
options included in the HH package. If you don't already have the HH
package, you can get it with
install.packages(HH)
Graphically, you can plot them with the function
interaction2wt(..., simple=TRUE)
See the examples in
The grouped boxplot is one of the features included in the HH package.
An example is posted on my site
http://astro.ocis.temple.edu/~rmh/HH/bwplot-color.pdf
See also the R-help email with an example vaguely similar to yours:
https://stat.ethz.ch/pipermail/r-help/2009-March/190541.html
All the examples have the code file that generate them listed in the
captions. The specific panel function that is usually used is
panel.bwplot.intermediate.hh
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PLEASE
The boxplot with sample size information is one of the features
included in the HH package.
An example is posted on my site
http://astro.ocis.temple.edu/~rmh/HH/bwplot-color.pdf
In this example I show grouping, control of x-axis position, multiple
x-axis labels, and
control of display of extreme
The grouped boxplot is one of the features included in the HH package.
An example is posted on my site
http://astro.ocis.temple.edu/~rmh/HH/bwplot-color.pdf
Reconstructing Figure 3 in your file GroupedBoxplot.pdf from your
11/24/2009 10:35 AM email would be easy.
## Your original data is already the result of table().
## Here are two versions, one using barchart and one barplot.
tmpc - textConnection(
Month Core(%) Non_core(%)
1 4555
2 4852
3 3664
4
Please also look at the R document
http://www.r-project.org/doc/R-FDA.pdf
and ask your IT department to read this document
Rich
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PLEASE do read the posting guide
?panel.barchart
use the argument
origin=0
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and provide commented, minimal, self-contained,
The row names are not constructed in 2.10.0pat. Is this change intentional?
I am using Windows.
R version 2.10.0 Patched (2009-11-09 r50375)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
contrasts(ordered(LETTERS[1:4]))
contrasts(ordered(LETTERS[1:4]))
## You can do this with the qr functions.
tmp - rnorm(4)
tmp.qr - qr(tmp)
tmp.complete - qr.Q(tmp.qr, complete=TRUE)
tmp.complete[,1] / tmp
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PLEASE do read the posting
install.packages(HH)
library(HH)
?MMC
Go to the bottom of the page and read the maiz example.
Read through the example that shows aovlist objects don't work
and how to construct the equivalent aov object.
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tmp - cbind(x=c(1,-.2,.3,.4),
y=c(.5,.6,-.7,.8))
row.names(tmp) - letters[1:4]
barchart(tmp,
horizontal=FALSE,
stack=TRUE,
auto.key=list(
title=pollutant,
border=TRUE),
xlab=Month,
main=Interesting Plot)
barchart(tmp,
Robert Terwilliger wrote:
Dear R experts,
I have a so-called person-level data frame that I need to transform
into a person-period data frame.
If the lingo is unclear, the data have one row for each subject, with
repeated measures data each in a separate column.
I need to transform these data
Unexpected symbol often means missing punctuation.
In this case, it looks like
panel=function(){panel.xyplot(Kalibrierung$Spannung,Kalibrierung
$Magnetfeld)panel.abline(reg=test)}
this argument is missing a semi-colon ; before panel.abline.
The first step is to make Weather a factor. Then the levels would be displayed
in the strip labels.
The second step would be to change the level values to the actual strings
you want to see.
tmp - data.frame(Weather=1:3, x=rnorm(3), y=rnorm(3))
xyplot(y ~ x | Weather, data=tmp)
tmp$Weather -
Bastian Pöschl wrote:
Dear useRs,
I search for a possibillity to plot stacked bars at specific x positions.
I tried and tried, but the only way i got something adequate was by using
lowlevel plots segments(). That is quiet ok, but will not please eyes without a
lot of par() lines.
Stavros Macrakis wrote:
I could of course write my own print function for this, but was
wondering if there was a standard way of doing it. If not in R,
perhaps there is some way to have ESS delete the final spaces?
ESS, or more precisely emacs, can handle that. Use the M-x
On Wed, Nov 11, 2009 at 8:12 PM, Stavros Macrakis macra...@alum.mit.edu wrote:
Thanks for the suggestion. I'mm familiar with the truncate-lines variable,
but that's not quite what I was looking for. I don't want the padding
spaces displayed, but I do want to see long strings at the end of the
qwe84 wrote:
Hello, I'm a totally newbie to R and I'm taking a class using S+.
In the class we use the multcomp command which takes a aov object and
calculates confidence intervals for all pairwise differences by the Fisher
least significant differences method.
How can I do this in R.
Thank
Please see the maiz example in ?HH:::glht.mmc
You may need to install HH first with
install.packages(HH)
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Lines sent to R by C-c C-n and related commands are excluded
from the R history. They appear only in the ESS history.
This, along with everything else, is documented in the file
/ess/doc/html/ess.html
Questions on ESS should be sent to the ESS list
ess-h...@stat.math.ethz.ch
Rich
Use the lgamma function.
log(gamma(170))
[1] 701.4373
lgamma(170)
[1] 701.4373
In typical uses of gamma(), they are multiplied or divided
by other gamma() values, bringing the final result into the
range of double precision numbers.
Also, look at beta(), which does those divisions of
ESS does everything you requested.
ess.r-project.org
ess-remote is the specific feature that allows you to run a program
on another computer from within a buffer on the local computer.
Rich
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I think its a problem with my data, something about how Rexcel
imported it
We don't have enough information to be sure. My guess is that your
data in Excel is integers which are intended to be levels of a factor.
Excel doesn't distinguish between integers and integers that might be
factor
Now I am worried that you have a wrong analysis.
the aov function is perfectly happy using either factors or
numeric variables. Are there really only two levels of time,
which is what one degree of freedom for time suggests? Or are there
more than two level, but since aov() sees that as a
z - abind(x[,,1], c(4,5,6),along=0)
z is probably not what you want because you aren't using the drop=FALSE
argument. See the FAQ 7.5
abind, and arrays in general, are rectangular solids. They are not
ragged. For that you need lists. To get something like your request
x
, , 1
library(abind) ## array binding
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and provide commented, minimal, self-contained, reproducible
points(x[4,],pch=2)# this is plotted as two points
drops what it sees as an unnecessary dimension.
Use
points(x[4,, drop=FALSE], pch=2)
See FAQ 7.5
tmp - matrix(1:2)
tmp
tmp[,1]
tmp[,1,drop=FALSE]
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Jesse Poland wrote:
I would like to combine multiple pairs plots (each one being a matrix
of correlation plots) into a single graphic. I have tried the par()
function, which works well to combine several simple graphs. However,
the pairs() graph seems to override the par() function and produce
On Thu, Oct 15, 2009 at 4:56 PM, Peng Yu pengyu...@gmail.com wrote:
Can somebody point me a book on Fisher's exact test? I looked a few
webpages. But the descriptions on the webpages are not very complete.
Is there a book on that covers all the aspect of Fisher's exact test
that is implemented
I don't understand the context of the question.
Since the data is already in R, you should use it from within
R. What is the reason for translating it to XML and then back?
You take the risk of two levels of distortion.
I am guessing that you want continuity of your work over multiple
login
## Paul
## I think you are looking for interaction2wt
y - rnorm(36)
f1 - rep(c(after, before), 18)
f2 - rep(1:3, 12)
f3 - rep(1:2, each=18)
## your definition of ff was faulty. It gave a constant.
f3.f1 - interaction(f3, f1)
interaction.plot(f3.f1, f2, y)
f2 - factor(f2)
f3 - factor(f3)
##
tmp - data.frame(matrix(nrow=0, ncol=32))
tmp
[1] X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17
X18 X19
[20] X20 X21 X22 X23 X24 X25 X26 X27 X28 X29 X30 X31 X32
0 rows (or 0-length row.names)
names(tmp) - c(letters, LETTERS[1:6])
tmp
[1] a b c d e f g h i j k l m n o p
tmp2 - matrix(1:8,4,2)
dimnames(tmp2)
NULL
tmp2
[,1] [,2]
[1,]15
[2,]26
[3,]37
[4,]48
dimnames(tmp2)[[2]] - c(a,b)
tmp2
a b
[1,] 1 5
[2,] 2 6
[3,] 3 7
[4,] 4 8
tmp1 - matrix(1:4,4,1)
dimnames(tmp1)
NULL
tmp1
[,1]
[1,]1
[2,]2
[3,]3
It is easier in lattice
dp - c(1,4,3,2,5,7,9,8,9,2)
tp - 1:10
gg - rep(1:3, c(3,3,4))
ddff - data.frame(dp=dp, tp=tp, gg=gg)
xyplot(dp ~ tp, groups=gg, data=ddff)
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PLEASE
If you are starting with an Excel file, then you should have R read
the xls file directly.
You should avoid the distortions often introduced by an intermediate
format such as .txt or .csv files.
I recommend using RExcel. You can get it from CRAN with
install.packages(RExcelInstaller)
See the documentation for ESS in the ESS distribution
ess/doc/html/readme.html
There is even more detail in
ess/doc/html/ess.html
For the specific question about the emacs initialization file ~/.emacs,
that file is in your home directory which emacs will find.
The ~ abbreviation is required
exp(seq(log(1.4), log(30), length=11))
[1] 1.40 1.902074 2.584203 3.510961 4.770076 6.480741
8.804891 11.962537 16.252591 22.081162
[11] 30.00
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There are two issues here.
The specifics of the error message are because you declared
a data.frame with 0 columns and then attempted to change two
columns.
data.frame()
data frame with 0 columns and 0 rows
q - data.frame()
q[1,] - data.frame(a=3, b=6)
Warning in `[-.data.frame`(`*tmp*`, 1,
Peter,
Thank you for the dput values.
Kenn points out that
result - cbind(data1[,,1], data2[,,1])
dim(result) - c(3,3,1)
gets what you want.
We wrote abind to bind atomic arrays and/or data.frames. The list
feature, which is interfering with your usage,
was designed to simplify calling
Almost certainly, abind is what you need for the task.
Please dput() your matlab objects and send that to the list.
That will make your example reproducible.
Rich
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This is where a good editor with proper syntactic indentation is helpful.
The first example is Terry's function as indented by ESS. It is very
clear that there are two lines with parallel indentation.
zed - function(x,y,z) {
x + y
+z;
}
The second function is modified to place the + on the
1. The embedded blanks often cause problems. Try the 8.3 version of the
filepath. To find the 8.3 name, open an MSDOS cmd window and enter
dir /x 'C:\\Raoul\\R
There will be a line something like
RMAPS_~1 R Maps_UK Maps_Test
Use the value that appears in the RMAPS_~1 position.
2. try
Ok, now we can talk.
1. covariates: coon
Your model specification put coon sequentially last, effectively testing
the hypothesis that the slope associated with coon, after
adjusting for all the factors, is zero.
My model place coon sequentially first, effectively testing the
hypotheses that
The three-way interactions you mention are included in the model formula
I suggested. If they didn't appear in the expansion, it suggests
that you have some aliasing due to empty cells.
I can't do any more without your dataset.
You can post your dataset with random response values.
The exact
Your email program truncated the model. It would not run,
hence was not reproducible.
The last few characters of the first line are
+Error(block/plot,
which is syntactically impossible because there is no
closing parenthesis before the comma.
Try executing your email and see the difficulty.
Your model formula cannot be correct.
The phrase
Error(block/plot, data = track)
is wrong.
It has to be something like this
Error(block/plot), data = track
The Error function requires a well-defined formula.
The , character cannot be inside the Error function.
You misunderstood my use of
Yes, I meant summary(). anova() isn't defined for aovlist objects and
summary() is.
Warning message:
In aov(kotz.mice ~ kotz.coon + block * veget * fruit * time -
block:veget:fruit:time + :
Error() model is singular
You will need to investigate the singular Error() model. You might
track.aov - aov(mice ~ coon
+ block*veget*fruit*time - block:veget:fruit:time
+ Error(block/plot), data = track)
anova(track.aov)
I think this is what you are looking for. This model in words says,
What is the effect of the four-way crossing after adjusting
Jean-Paul Maalouf wrote:
Do you have any idea on how can I verify preliminary assumptions in
this model (normality of the residuals and variance homogeneity),
since R is not able to extract residuals?
Of course, R extracts residuals. Use the proj() function. See ?proj
for the example
to
Ping-Hsun Hsieh wrote:
Dear R- experts,
I am trying to superimpose two or more scatterplot matrices generated by
pairs() to visualize the differences over each datasets, but have not been very
successful. Two data frames, df1 and df2 for example, each has the same five
variables in
I think you are asking for Reduce
Reduce(`+`, a)
[,1] [,2] [,3]
[1,]300
[2,]030
[3,]003
You might be asking for do.call with some function's name as its first
argument.
do.call(sum, a)
[1] 9
__
Look at the anova.mean function in the HH package.
It does what you are asking, although limited to one-way ANOVA.
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Try this
Rich
tmp - data.frame(
y=rnorm(100),
category=rep(factor(letters[1:5]),each=20),
level=rep(factor(0:1), length=100))
tmp
table(tmp[,2:3])
tmp$y[with(tmp, category==a level=0)] - NA
tmp$y[with(tmp, category==a level==0)] - NA
tmp$y[with(tmp, category==e level==1)] - NA
tmp$y[78:80]
I think you are looking for mosaic()
table(df)
library(vcd)
mosaic(outcome ~ group, data=df)
Rich
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Alan Izenman suggests:
I have lots of places worth checking out for him. It means a lot
of reading.
Probably the first (and best) place to start is the set of Springer
books entitled Breakthroughs in Statistics, which was edited by Kotz
Johnson. There' are three (3) volumes:
tmp.out.sort - tmp.out[, order(names(tmp.out))]
tmp.out.sort - tmp.out[, order(names(tmp.out)), drop=FALSE]
From your description of misbehavior with a single column,
I think the drop=FALSE argument will provide the protection you need.
Then you will not need the if clause.
See
?`[.data.frame`
This is an eigenvalue problem with 0 on the main diagonal.
It is almost always inefficient to find the determinant
as an intermediate step. The original poster is looking for the
ngative of the eigenvalues of the matrix with the x replaced by zeros.
tmp -
## you may need to
## install.packages(HH)
library(HH)
tmp - data.frame(y=rnorm(500),
g=rep.int(c(A, B, C, D), 125),
a=factor(rbinom(500, 1, .5)))
bwplot(y ~ g | a, data=tmp)
bwplot(y ~ a | g, data=tmp)
tmp$ga - with(tmp, interaction(a, g))
tmp - data.frame(y=rnorm(15000),
x1 - factor(sample(48, 15000, replace=TRUE)),
z1 - factor(sample(242, 15000, replace=TRUE)))
system.time(
tmp.aov - aov(y ~ x1/z1, data=tmp)
)
## exceeds memory
tmp2 - data.frame(y=rnorm(15000),
Yes, download the HH package from CRAN and then see
?HH::orthog.complete
for the function description and several examples.
Rich
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of megh
Sent: Sunday, January 11, 2009 19:29
To:
I believe you are looking for the summary.lm() function and its split=
argument.
Look at
example(summary.aov)
for several examples.
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PLEASE do read the posting guide
The function ... works for different values of two
Thomas Lumley
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented,
x - matrix(rnorm(1:20), 5, 4)
x.qr - qr(x)
Q - qr.Q(x.qr)
R - qr.R(x.qr)
X - qr.X(x.qr)
Q
R
X
Q %*% R
qr.Q(x.qr, complete=TRUE) ## orthogonal completion
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PLEASE do read
I suggest the panel.dotplot.tb in the HH package.
It is a lattice panel function and therefore works
with standard trellis formulas including conditioning
variables and grouping variables.
library(HH)
example(panel.dotplot.tb)
Since you define what you want in terms of Minitab, I mention
that
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