Displaying 20 results from an estimated 1100 matches similar to: "modification of the function ecdf"
2005 Nov 02
2
help with the coordinates of the ECDF object
Hi all R users
I would like to know how acess the coordinates
of the ECDF object.
I look for the example,
in this part:
######################
print(ls.Fn12 <- ls(env= environment(Fn12)))
######################
but I do not know to extract
the Y coordinate and put it in other variable.
My objective is to make a plot
and identify the points with labels.
############# Example by
2007 May 30
1
Sort in ecdf
Hi!
I've noticed the ecdf() R code (R ver. 2.5.0) contains two call to sort:
--- [R-code] ---
ecdf <- function(x)
x <- sort(x)
n <- length(x)
if (n < 1)
stop("'x' must have 1 or more non-missing values")
vals <- sort(unique(x))
rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n,
method
2006 Jan 18
0
R: ecdf - linear
I'm replying to R-devel, the mailing list which should be used
to discuss R feature enhancements.
>>>>> "Norman" == Norman Warthmann <norman at warthmann.com>
>>>>> on Wed, 18 Jan 2006 11:33:22 +0100 writes:
Norman> ..........
Norman> Is there a specific reason why in the ecdf-function
Norman> the variable
2008 Jan 11
1
Adding weights to ecdf
I would like you consider that the function ecdf
could be extended in the following way to handle weights
when computing Empirical distribution Functions. There
exist particular cases that supports this kind of
extension, see for example:
Rao, C. R., 1997.
Statistic and True. Putting chance to work.
World Scientific Publishing.
Cox, D. R., 1969.
Some Sampling Problems in Technology.
New
2004 Mar 17
0
Plot 2 time series with different y axes (left and right)
Petr Pikal said:
> I am not really a R specialist but for this task I use function:
and he pasted his code into the email. I reindented the code, and
wrote a fragment to experiment with it. Here it is:
---------------------------------------------------------------------------
plot.yy <- function(x, yright, yleft,
yleftlim=NULL, yrightlim = NULL,
2010 Aug 25
3
approxfun-problems (yleft and yright ignored)
Dear all,
I have run into a problem when running some code implemented in the
Bioconductor panp-package (applied to my own expression data), whereby gene
expression values of known true negative probesets (x) are interpolated onto
present/absent p-values (y) between 0 and 1 using the *approxfun -
function*{stats}; when I have used R version 2.8, everything had
worked fine,
however, after updating
2017 Nov 23
0
adding percentage secondary y-axis
Hi
It is usually not recommended but if you insist
maybe
library(plotrix)
?twoord.plot
twoord.plot(lx=D[,1],ly=D[,2], rx=D[,1], ry=D[,3])
or
plot.yy(x=D[,1],yright=D[,3], yleft=D[,2])
which allows only one x axis (see below).
Cheers
Petr
plot.yy <- function (x, yright, yleft, yleftlim = NULL, yrightlim = NULL,
xlab = NULL, yylab = list(NA, NA), pch = c(1, 2),
col = c(1,2), linky
2017 Nov 23
2
adding percentage secondary y-axis
Thank you very much peter.
It worked out nicely.
I have additional question. How can I get Y-axis on log-scale?
Thank you very much in Advance,
Eliza
UoS
PP
________________________________
From: PIKAL Petr <petr.pikal at precheza.cz>
Sent: 23 November 2017 16:22:39
To: Eliza Botto; r-help at r-project.org
Subject: RE: adding percentage secondary y-axis
Hi
It is usually not
2008 Jul 20
3
asp and ylim
#See David Williams' book "Weighing the odds", p286
y <- c(1.21, 0.51, 0.14, 1.62, -0.8,
0.72, -1.71, 0.84, 0.02, -0.12)
ybar <- mean(y)
ylength <- length(y)
ybarv <- rep(ybar, ylength)
x <- 1:ylength
plot(x,y,asp=1,xlab="position",ylab="ybar",type="n",ylim=c(-1,1))
segments(x[1], ybar, x[ylength], ybar)
segments(x,ybarv,x,y)
2004 Oct 17
3
ecdf with lots of ties is inefficient (PR#7292)
Full_Name: Martin Frith
Version: R-2.0.0
OS: linux-gnu
Submission from: (NULL) (134.160.83.73)
I have large vectors containing 100,000 to 20,000,000 numbers. However, they
only contain a few hundred *distinct* numbers (e.g. positive integers < 200).
When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot
the ecdf with postscript, the output is unnecessarily bloated
2007 Mar 15
1
How to use result of approxfun in a package?
I am working on a project where we start with start with 2 long,
equal-length vectors, massage them in various ways, and end up with a
function mapping one interval to another. I'll call that function
"f1." The last step in R is to generate f1 as the value of the
approxfun function. I would like to put f1 into a package, but
without having the package redo the creation of
2006 Jul 17
3
information about a function
Hi people,
I am new in this list and could not find a FAQ for it in particular,
furthermore I could not find my question answered in the official R
FAQ or docs.
I have simply something like this:
> f<-approxfun(data[,1],data[,2])
and f is:
> f
function (v)
.C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v),
as.integer(length(v)),
How to count from larger value to smaller value in ecdf (Empirical Cumulative Distribution Function)
2008 Feb 19
1
How to count from larger value to smaller value in ecdf (Empirical Cumulative Distribution Function)
Hi, all
ecdf function (Empirical Cumulative Distribution Function) in "stats"
package counts from smaller values to larger values.
However, I want to draw it by counting from larger value to smaller values
and I couldn't find options for this purpose.
How can I draw ecdf or ecdf like graph by counting from larger values to
smaller values.
Thank you in advance.
Hyunchul Kim
2013 Feb 14
1
approxfun values
Readers,
According to the help '?approxfun', the function can be used to obtain
the interpolated values. The following test was tried:
> testinterpolation<-read.csv('test.csv',header=FALSE)
> testinterpolation
V1 V2
1 10 2
2 20 NA
3 30 5
4 40 7
5 50 NA
6 60 NA
7 70 2
8 80 6
9 90 9
10 100 NA
>
2009 Mar 25
5
histogram plots with many different samples
Dear R users,
I would like to draw some histograms as seen in the page whose address I
wrote below. I searched through the web a lot and I found a page which
describes how I can do it for older versions of R. For newer versions they
recommend to install the package R.basics in R.clusters but this does not
exist. The address of the web page is
http://www1.maths.lth.se/help/R/plot.histogram/
2009 Feb 04
3
chi squared goodness of fit test with R
Dear R users,
I am a master student in Mathematics and I am writing my thesis in
statistics. I need to use R and unfortunately I do not have any experience
with a computer program. Could you please help me about chi squared goodness
of fit test with R? In R-help website I saw a message about how to do that
but I do not know how to cut the data into bins and calculate the expected
numbers in each
1997 Oct 08
0
R-alpha: dump() / dput() -- fail for "environmental" and attributed functions
Here is a simple example to show what I mean:
f1 <- approxfun(1:3, 2:4)
dump("f1", file="")
which yields (in current development snapshot;
other versions are conceptually equivalent)
"f1" <-
function (v)
.C("approx", as.double(x), as.double(y), n, xout = as.double(v),
length(v), as.integer(method), as.double(yleft),
2009 Jul 21
1
bug in approx crashes R
Dear R-devel,
The following line crashes R
> approx(1, 1, 0, method='const', rule=2, f=0, yleft=NULL, ties='ordered')$y
Process R:2 exited abnormally with code 5 at Tue Jul 21 14:18:09 2009
> version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 9.1
year
2007 Apr 23
0
New version of actuar
UseRs,
actuar is a package for Actuarial Science. A rather preliminary
version (0.1-3) of the package has been available on CRAN since February 2006.
We now announce the immediate availability of version 0.9-2 sporting a large
number of new features.
Non actuaries behold! There can be some features of interest for you,
especially those related to new probability distribution and to the
2007 Apr 23
0
New version of actuar
UseRs,
actuar is a package for Actuarial Science. A rather preliminary
version (0.1-3) of the package has been available on CRAN since February 2006.
We now announce the immediate availability of version 0.9-2 sporting a large
number of new features.
Non actuaries behold! There can be some features of interest for you,
especially those related to new probability distribution and to the