With lrm.fit you are fitting a completely different model. One of the
things lrm does, is preparing the input for lrm.fit which in this case
means that dummy variables are generated for categorical variables such
as 'KILLIP'.
The error message means that model did not converge after the maxi
You can also inadvertently transmit data to the internet using a package
without being obviously 'stupid', e.g. by using a package that uses an
external service for data processing. For example, some javascript
visualisation libs can do that (not sure if those wrapped in R-packages
do), or, for
Or
testdf <- testdf[FALSE, ]
or
testdf <- testdf[numeric(0), ]
which seems to be slightly faster.
Best,
Jan
Op 27-9-2018 om 10:32 schreef PIKAL Petr:
Hm
I would use
testdf<-data.frame(A=c(1,2),B=c(2,3),C=c(3,4))
str(testdf)
'data.frame': 2 obs. of 3 variables:
$ A: num 1 2
$ B:
Using another implementation of the gower distance:
library(gower)
gower_dist(iris[1,], iris)
HTH,
Jan
On 26-10-18 15:07, Aerenbkts bkts wrote:
I have a data-frame with 30k rows and 10 features. I would like to
calculate distance matrix like below;
gower_dist <- daisy(data-frame, metr
distance for the first 5 rows.
but it did not work. Do you have any suggestion about it?
On Fri, 26 Oct 2018 at 21:31, Jan van der Laan <mailto:rh...@eoos.dds.nl>> wrote:
Using another implementation of the gower distance:
library(gower)
gower_dist(iris[1,], iris)
Below a similar example, using sf and leaflet; plotting the trajectory
on a background map.
library(leaflet)
library(sf)
library(dplyr)
# Generate example data
gen_data <- function(id, n) {
data.frame(
id = id,
date = 1:n,
lat = runif(10, min = -90, max = 90),
lon = runif(10,
Are you sure you didn't do saveRDS("rawData", file = "rawData.rds")
instead of saveRDS(rawData, file = "rawData.rds") ? This would explain
the result you have under linux.
In principle saveRDS and readRDS can be used to copy objects between
R-sessions without loosing information.
What doe
First, the file does contain 302 columns; the variable layout
(http://www.cdc.gov/brfss/annual_data/2006/varlayout_table_06.htm)
contains 302 columns. So, reading the SASS file probably works correctly.
Second, the read.asc function you use is for reading geographic raster
files, not fixed wid
I have some questions about the use of weights in binomial glm as I am
not getting the results I would expect. In my case the weights I have
can be seen as 'replicate weights'; one respondent i in my dataset
corresponds to w[i] persons in the population. From the documentation
of the glm method, I
form a post-mortem examination: he may be able to
> say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reason
to bad default starting values
> for the iteration. You need either to specify the data as recommended or
> supply starting values.
>
> =thomas
>
>
> On Fri, 16 Apr 2010, Jan van der Laan wrote:
>
>> I have some questions about the use of weights in binomial glm as I am
>
Something like this?
# Remove everything after ; to give the status
status<- sub(';.*$', '', data$cancer.problems)
# Remove everything before the last ; to give tissue
# In case a no ; in the string this goes wrong; correct
tissue<- sub('^.*;[ \n]*', '', data$cancer.problems)
tissue[! gre
When you just want to calculate the probability of belong to class A
or B of a new observation xi and do not have to do any new model
estimations or other analyses, the easiest way is probably to write
the estimated coefficients to a text write and read them in in your
java/c/whatever program and u
Giovanni,
You can use the '...' for that, as in:
loocv <- function(data, fnc, ...) {
n <- length(data.x)
score <- 0
for (i in 1:n) {
x_i <- data.x[-i]
y_i <- data.y[-i]
yhat <- fnc(x=x_i,y=y_i, ...)
score <- score + (y_i - yhat)^2
}
score <- score/n
return(score)
}
scoreks <- l
Alejandra,
If it was initially working ok, I would first check with the IT
department if there has been a change to the configuration of the
firewall, virus scanners, file system etc. as these can affect the
performance of R-studio. R-studio uses a client-server setup on your
machine, so a fi
I would actually go a step in the other direction: per project
libraries. For example by adding a .Rprofile file to your project
directory. This ensures that everybody working on a project uses the
same version of the packages (even on different machines e.g. on shared
folders).
This can g
But even if you could have a generator that is superefficient and
perform an calculation that is superfast the number of elements is
ridiculously large.
If we take 1 nanosec per element; the computation would still take:
> (100^10)*1E-9/3600
[1] 2778
hours, or
> (100^10)*1E-9/3600/24/
This is an optimisation problem that you are trying to solve using a
grid search. There are numerous methods for optimisation, see
https://cran.r-project.org/web/views/Optimization.html for and overview
for R. It really depends on the exact problem what method is appropriate.
As Petr said h
read_fst is from the package fst. The fileformat fst uses is a binary
format designed to be fast readable. It is a column oriented format and
compressed. So, to be able to work fst needs access to the file itself
and wont accept a file connection as functions like read.table an
variants ac
What you could also try is check if the self coded functions use the
random generator when defining them:
starting_seed <- .Random.seed
Step 1. Self-coded functions (these functions generate random numbers as
well)
# check if functions have modified the seed:
all.equal(starting_seed, .Ra
True, but in a lot of cases where a python user might use a dict an R
user will probably use a list; or when we are talking about arrays of
dicts in python, the R solution will probably be a data.frame (with each
dict field in a separate column).
Jan
On 02-11-2021 11:18, Eric Berger wro
e a data.frame with
multiple columns with the same name. But as Duncan Murdoch mentions you
can usually control for that.
Best,
Jan
On 02-11-2021 11:32, Yonghua Peng wrote:
But for data.frame the colnames can be duplicated. Am I right?
Regards.
On Tue, Nov 2, 2021 at 6:29 PM Jan van der L
(listOfValues, parent = emptyenv())
Hope this helps!
On Tue, Nov 2, 2021, 06:49 Yonghua Peng wrote:
But for data.frame the colnames can be duplicated. Am I right?
Regards.
On Tue, Nov 2, 2021 at 6:29 PM Jan van der Laan
wrote:
True, but in a lot of cases where a python user might use a
Have a look at the base functions tapply and aggregate.
For example see:
-
https://cran.r-project.org/doc/manuals/r-release/R-intro.html#The-function-tapply_0028_0029-and-ragged-arrays
,
- https://online.stat.psu.edu/stat484/lesson/9/9.2,
- or ?tapply and ?aggregate.
Also your current code se
For visualising hierarchical data a treemap can also work well. For
example, using the treemap package:
n <- 1000
library(data.table)
library(treemap)
dta <- data.table(
level1 = sample(LETTERS[1:5], n, replace = TRUE),
level2 = sample(letters[1:5], n, replace = TRUE),
level3 = sample(1:
You're sure the extra column is indeed an extra column? According to the
documentation
(https://artefacts.ceda.ac.uk/badc_datadocs/ukmo-midas/RH_Table.html)
there should be 15 columns.
Could it, for example, be that one of the columns contains records with
commas?
Jan
On 29-09-2022 15:54
You could try to see what stattransfer can make of it. They have a free
version that imports only part of the data. You could use that to see if
stattransfer would help and perhaps discover what format it is in.
HTH
Jsn
On 16-01-2023 23:22, Joseph Voelkel wrote:
Dear foreign maintainers and
Hi Avi, list,
Below an alternative suggestion:
func <- function(a, b, c) {
list(a, b, c)
}
1:3 |> list(x = _) |> with(func(a, x, b))
Not sure if this is more readable than some of the other solutions, e.g.
your solution, but you could make a variant of with more specific for
this use case
Perhaps the ragg package? That has an `agg_capture` device "that lets
you access the device buffer directly from your R session."
https://github.com/r-lib/ragg
HTH,
Jan
On 28-05-2023 13:46, Duncan Murdoch wrote:
Is there a way to open a graphics device that plots entirely to an array
or
The dredge function has a `extra` argument to get other statistics:
optional additional statistics to be included in the result, provided as
functions, function names or a list of such (preferably named or
quoted). As with the rank argument, each function must accept as an
argument a fitted mo
Shorter/simpler alternative for adding a alpha channel
adjustcolor("lightblue", alpha = 0.5)
So I would use something like:
# Open new plot; make sure limits are ok; but don't plot
plot(0, 0, xlim=c(1,20),
ylim = range(c(mean1+sd1, mean2+sd2, mean1-sd1, mean2-sd2)),
type="n", las=1,
xla
Does adding
, show.legend = c("color"=TRUE, "fill"=FALSE)
to the geom_point do what you want?
Best,
Jan
On 06-10-2023 11:09, Chris Evans via R-help wrote:
library(tidyverse)
tibble(x = 2:9, y = 2:9, c = c(rep("A", 5), rep("B", 3))) -> tmpTibPoints
tibble(x = c(1, 5, 5, 1), y = c(1, 1, 5, 5)
B" = "grey",
"C" = "green"),
labels = c("Deteriorated",
"No change",
"Improved")) +
scale_fill_manual(name = "Change"
thing
about these issues though I do hit problems exchanging things with my
Spanish speaking
colleagues). Jan or anyone: any simple reassurance or pointers to
resources I should
best use for homework about these issues?
TIA (again!)
Chris
On 06/10/2023 12:55, Jan van der Laan wrote:
You are
I believe mapshaper has functionality for removing small 'islands'.
There is a webinterface for mapshaper, but I see there is also an
R-package (see
https://search.r-project.org/CRAN/refmans/rmapshaper/html/ms_filter_islands.html
for island removal).
If you want to manually select which islan
I don't know how many files you are planning to open, but what you
also might run into is the maximum number of connections namely 125.
See ?file.
Jan
mohan.radhakrish...@polarisft.com schreef:
Hi,
I thought that 'R' like java will allow me to store file names
(keys) and file d
Dear Christian,
Well... it shouldn't normally do that. The only way I can currently
think of that might cause this problem is that the file has \r\n\r\n,
which would mean that every line is followed by an empty line.
Another cause might be (although I would not really expect the results
you
What probably is the problem is that read.table.ffdf uses the nrows
argument to read the file in chunks. However, read.fwf doesn't use a
nrow argument but a n argument.
One (non tested) solution is to write a wrapper around read.fwf and pass
this wrapper to read.table.ffwf. Something like:
89
Fax +41 31 323 43 21
christian.kame...@astra.admin.ch
www.astra.admin.ch
-Ursprüngliche Nachricht-
Von: Jan van der Laan [mailto:rh...@eoos.dds.nl]
Gesendet: Mittwoch, 7. August 2013 20:57
An: r-help@r-project.org
Cc: Kamenik Christian ASTRA
Betreff: Re: [R] laf_open_fwf
Dear Christian
admin.ch
-Ursprüngliche Nachricht-
Von: Jan van der Laan [mailto:rh...@eoos.dds.nl]
Gesendet: Freitag, 9. August 2013 10:01
An: Kamenik Christian ASTRA
Betreff: Re: AW: AW: [R] laf_open_fwf
Christian,
It seems some of the lines in your file have additional characters at the end
causing the line
You could use the fact that scan reads the data rowwise, and the fact
that arrays are stored columnwise:
# generate a small example dataset
exampl <- array(letters[1:25], dim=c(5,5))
write.table(exampl, file="example.dat", row.names=FALSE. col.names=FALSE,
sep="\t", quote=FALSE)
# and re
apply((t(as.matrix(b)) * a), 2, sum)
should do what you want.
Why this works; see,
http://cran.r-project.org/doc/manuals/r-release/R-intro.html#The-recycling-rule and the paragraph before
that.
Jan
Tammy Ma schreef:
HI,
I have the following question:
Vector a with lenght 150
A B
Have a look at the system command:
?system
HTH,
Jan
On 03/16/2013 10:09 PM, Sedat Sen wrote:
Dear list,
I want to run a statistical program (using its .exe file) from R by
writing a script. I know there are some packages that call WinBUGS, Mplus
etc. form R. I just want to call the .exe
I believe it was already mentioned, but I can recommend the LaF package
(not completely impartial being the maintainer of LaF ;-)
However, the speed differences between packages will not be very large.
Eventually all packages will have to read in 6 GB of data and convert
the text data to num
Some colleagues ran into similar problems after migrating to windows 7.
They could no longer install packages in certain network locations
because the read only bit was set (which could be unset after which
windows set it again). Perhaps the following helps:
http://itexpertvoice.com/home/fi
Characters in R are zero terminated (although I couldn't find that in
the R extensions manual). So, you could use:
void dealWithCharacter(char **chaine, int *size){
Rprintf("The string is '%s'\n", chaine[0]);
}
Jan
On 05/10/2013 03:51 PM, cgenolin wrote:
Hi the list,
I include some C c
It doesn't seem possible to index an ff-vector using a logical
ff-vector. You can use subset (also in ffbase) or first convert 'a' to
a normal logical vector:
library(ff)
library(ffbase)
data1 <- as.ffdf(data.frame(a = letters[1:10], b=1:10))
data2 <- as.ffdf(data.frame(a = letters[5:26
Did not see a simple way to make it faster. However, this is a piece of
code which can be made to run much faster in C. See below.
I don't know if you are familiar with running c-code from R. If not, the
official documentation is in the R Extensions manual. However, this is
not the most easy
I have a r-script (rook.R) that starts a Rook server. To present users
from having to start R and type in source("rook.R"), I want to create
a bash script and bat file that starts R and sources the script.
However, to keep the Rook server running R should not close after
running the scrip
Or
ti <- aggregate(dataframename[paste0("y", 1:3)],
by=dataframename["aggregationvar"],
sum,na.rm=TRUE)
which gives you all results in one data.frame.
Jan
"MacQueen, Don" schreef:
Many ways. Here is one:
### supposing you have y1, y2, and y3 in your data frame
for (i in
I suspect it should be
my.data.copy <- dbReadTable(con, "week42")
(with con instead of tbs as first argument)
Jan
Tammy Ma schreef:
tbs<-dbListTables(con)
tbs
[1] "lowend" "time" "week30" "week33" "week39" "week42"
my.data.copy <- dbReadTable(tbs, "week42")
Error in function (cla
The following seems to work:
data = read.csv.ffdf(x=NULL,file="data.csv",nrows=1001,first.rows = 500,
next.rows = 1005,sep=",",colClasses = c("integer","factor","logical"))
'character' doesn't work because ff does not support character
vectors. Character vector need to be stored as factors.
Could it be that your r-script is saved in a different encoding than
the one used by R (which will probably be UTF8 since you're working on
linux)?
--
Jan
gerald.j...@dgag.ca schreef:
Hello,
I am using R, 2.15.2, on a 64-bit Linux box. I run R through Emacs' ESS.
R runs in a French,
Lorenzo,
You can also use a custom colorscale using color.scale and the
cellcolors option of color2D.matplot:
pdf("test_color_scale_logcolor.pdf")
oldpar<-par( mar = c(4.5,5, 2, 1) + 0.1,
cex.axis=1.4,cex.lab=1.6,cex.main=1.6)
cellcolors <- color.scale(log(A),c(0.2,1),c(0.2,0.5),c(0,0))
color2D.
Loukia,
Do you mean that the lines are wrapped when you open the file in
Notepad? Notepad seems to wrap lines after 1024 characters. Try to
open the file in a more decent editor, e.g. notepad++, gvim, ... and
there are probably plenty more editors available.
Hope this helps.
Jan
On Thu, Jul 1,
Dear list,
I get some strange results with daply from the plyr package. In the
example below, the average age per municipality for employed en
unemployed is calculated. If I do this using tapply (see code below) I
get the following result:
no yes
A NA 36.94931
B 51.2250
This is a bug, which I've fixed in the development version (hopefully
to be released next week).
In the plyr 1.2:
OK, thank you both for your answers. I'll wait for the next version.
Regards,
Jan
__
R-help@r-project.org mailing list
https://stat
You can also plot the +'s yourself using for example matlines:
# Some data
x <- 1:10
y <- 1:10
# Height and width of the crosses
dx1 <- 0.1 # width in negative x-direction
dx2 <- 0.2 # width in positive x-direction
dy1 <- 0.2 # height in negative y-direction
dy2 <- 0.3 # height in positive y-dir
Perhaps the following construct does what you need:
paste(c("a", "b", "c"), c(",", ":", ""), sep="",collapse="")
Regards,
Jan
On 29-10-2010 10:49, Ron Michael wrote:
> Hi all, I want to club different objects (character type) to a single one and
> using paste() function that can be done happ
Matt,
Below are three (of the probably many more) possible ways of doing this:
aggregate(1:nrow(df), df, length)
ftable(1 ~ f1 + f2, data=df)
library(plyr)
ddply(df, .(f1,f2), nrow)
Regards,
Jan
On 29-10-2010 15:53, Matthew Pettis wrote:
Hi,
I have a data frame with two factors (well, mo
Perhaps, the following construct does what you need:
paste(c("a", "b", "c"), c(",", ":", ""), sep="",collapse="")
Regards,
Jan
On 29-10-2010 10:49, Ron Michael wrote:
Hi all, I want to club different objects (character type) to a single one and using
paste() function that can be done happil
On 11/12/2010 09:23 AM, Santosh Srinivas wrote:
Dear Group,
Is there some way for me to package a few lines of R-code as exe and have it
running in the background? (unable to find info in the archives)
Even better if I can package it as an installation and send to my team who
do not have any b
Vincy,
I suppose the following does what you want. yy is now a list which
allows for differing lengths of the vectors.
> yy <- lapply(c(257, 520, 110), seq, to=0, by=-100)
> yy[[1]]
[1] 257 157 57
> yy[[2]]
[1] 520 420 320 220 120 20
Regards,
Jan
On 9-12-2010 11:40, Vincy Pyne wrote:
c(
You will have to modify your likelihood in such a way that it also
includes the weights. If your likelihood has the following form: l =
sum(log p_i) you could for example add the weights to the likelihood:
lw = sum(w_i * log p_i) (although I am not sure that this is the
correct way to add
iour?
I can of course remove the missing values myself before creating the
survey object. However, with many different variables with different
missing values, this is not very practical. Is there an easy way to
get the behaviour I want?
Thanks for your help.
With regards,
Jan van der Laa
Your problem is not completely clear to me, but perhaps something like
data <- data.frame(
a = rep(c(1,2), each=10),
b = rep(c('a', 'b', 'c', 'd'), 5))
library(plyr)
daply(data, a ~ b, nrow)
does what you need.
Regards,
Jan
On Wed, Aug 25, 2010 at 4:53 PM, rtsweeney wrote:
>
> Hi all,
>
Please, reply to the r-help and not only to me personally. That way
others can can also help, or perhaps benefit from the answers.
You can use strplit to remove the last part of the strings. strplit
returns a list of character vectors from which you (if I understand
you correctly) only want to sel
before creating the
survey object. However, with many different variables with different
missing values, this is not very practical. Is there an easy way to
get the behaviour I want?
Thanks for your help.
With regards,
Jan van der Laan
=== EXAMPLE ===
library(survey)
library(plyr)
# gen
Jim,
It is not completely clear how you want to handle the items in Array2,
but perhaps something like the following does what you needs (or at
least points you in the right direction):
paste(
rep(Array1, each=2),
rep(Array2[1], times=8),
rep(Array2[2:3], times=4),
sep='.')
Regard
Jan van der Laan :
I use the following code to create two data.frames d1 and d2 from a list:
types <- c("integer", "character", "double")
nlines <- 10
d1 <- as.data.frame(lapply(types, do.call, list(nlines)),
stringsAsFactor=FALSE)
l2 <
I use the following code to create two data.frames d1 and d2 from a list:
types <- c("integer", "character", "double")
nlines <- 10
d1 <- as.data.frame(lapply(types, do.call, list(nlines)),
stringsAsFactor=FALSE)
l2 <- lapply(types, do.call, list(nlines))
d2 <- as.data.frame(l2, s
On Sun, May 15, 2011 at 4:25 AM, Jan van der Laan wrote:
I use the following code to create two data.frames d1 and d2 from a list:
types<- c("integer", "character", "double")
nlines<- 10
d1<- as.data.frame(lapply(types, do.call, list(nlines)),
str
Gunter a écrit :
Inline below.
On Sun, May 15, 2011 at 11:11 AM, Jan van der Laan
wrote:
Thanks. I also noticed myself minutes after sending my message to the
list.
My 'please ignore my question it was just a stupid typo' message was sent
with the wrong account and is now awaiting mode
Perhaps you mean something like sapply or apply?
When d is indeed a data.frame with one column: sapply(d[,1], mash)
Regards,
Jan van der Laan
On Thu, May 20, 2010 at 12:47 AM, sedm1000 wrote:
>
> I hope that somebody can help me with this - I think very simple - issue...?
>
> I
The fact that your column names from your aggregate result contain multiple
numbers, suggests that something has gone wrong with reading your data in from
file. Have you had a look at your data.frame 'all'? Are BAR and X etc. numeric?
Judging from the 'c. etc' they aren't.
So, how do I aggr
One possible solution is to use something like:
a <- 0
for (i in 1:1E6) {
old.a <- a
# do something e.g.
a <- runif(1) < 1E-6
if (a != old.a) browser()
}
Another solution is to write your output to file (using sink for
example) and to watch this file using a tool like tail.
It has been a while back, but I believe I had to install libgtk2.0-dev
(that was on Ubuntu)
You could also try to install the r-cran-rgtk2 debian-package using
dpkg, aptitude, or whatever you use as package manager. This makes
rgtk available for all users.
HTH,
Jan
Quoting Lorenzo I
It has been a while back, but I believe I had to install libgtk2.0-dev
(that was on Ubuntu)
You could also try to install the r-cran-rgtk2 debian-package using
dpkg, aptitude, or whatever you use as package manager. This makes
rgtk available for all users.
HTH,
Jan
Quoting Lorenzo Isel
I have a categorical variable with a nested structure. For example,
region: a country is split into parts, which in turn contain
provinces, which contain municipalities:
Part -> Province -> Municipality
North
Province A
Municipality 1
Municipality 2
Municipality 3
There exists a non-breaking space:
http://en.wikipedia.org/wiki/Non-breaking_space
Perhaps you could use this. In R on Linux under gnome-terminal I can
enter it with CTRL+SHIFT+U00A0. This seems to work: it prints as a
space, but is not equal to ' '. I don't know if there are any
difficulties
There exists a non-breaking space:
http://en.wikipedia.org/wiki/Non-breaking_space
Perhaps you could use this. In R on Linux under gnome-terminal I can
enter it with CTRL+SHIFT+U00A0. This seems to work: it prints as a
space, but is not equal to ' '. I don't know if there are any
difficulties
What is the correct way to combine multiple calls to odfCat,
odfItemize, odfTable etc. inside a function?
As an example lets say I have a function that needs to write two
paragraphs of text and a list to the resulting odf-document (the real
function has much more complex logic, but I don'
examples in the package directory that explain this.
On Thu, Sep 15, 2011 at 8:16 AM, Jan van der Laan wrote:
What is the correct way to combine multiple calls to odfCat, odfItemize,
odfTable etc. inside a function?
As an example lets say I have a function that needs to write two paragraphs
of text and
Laura,
Perhaps the following example helps:
nbstr <- 100
result <- numeric(nbstr)
for (i in seq_len(nbstr)) {
# set the default value for when the current bootstrap fails
result[i] <- NA
try({
# estimate your cox model here
if (runif(1) < 0.1) stop("ERROR")
result[i] <- i
},
(as far as I can tell). Could you perhaps just tell me how I
should combine the output of multiple odf* calls inside a function?
Thanks again.
Jan
Quoting Max Kuhn :
formatting.odf, page 7. The results are in formattingOut.odt
On Thu, Sep 15, 2011 at 2:44 PM, Jan van der Laan wrote:
M
Michael,
You example doesn't seem to work. Append isn't passed on to the
write.table call. You will need to add a
Call$append<- append
to the function. And even then there will be a problem with the
headers that are repeated when appending.
An easier solution is to use write.table dir
Michael,
You example doesn't seem to work. Append isn't passed on to the
write.table call. You
will need to add a
Call$append<- append
to the function. And even then there will be a problem with the
headers that are repeated
when appending.
An easier solution is to use write.table dire
Michael,
You example doesn't seem to work. Append isn't passed on to the
write.table call. You will need to add a
Call$append<- append
to the function. And even then there will be a problem with the
headers that are repeated when appending.
An easier solution is to use write.table dire
can append row wise, so that it all stacks up
horizontally, the way you do it in xlswrite in matlab, where you can
even specify the cell number from where you want to write.
-Ashish
*From:*R. Michael Weylandt [mailto:michael.weyla...@gmail.com]
*Sent:* Thursday, September 22, 2011 1
Johan,
Your 'list' and 'array doubling' code can be written much more efficient.
The following function is faster than your g and easier to read:
g2 <- function(dotot) {
v <- list()
for (i in seq_len(dotot)) {
v[[i]] <- FALSE
}
}
In the following line in you array doubling function
The memisc package also offers functionality for documenting data.
Jan
On 06/22/2011 04:57 PM, Robert Lundqvist wrote:
Every now and then I realize that my attempts to document what all dataframes
consist of are unsufficient. So far, I have been writing notes in an external
file. Are there an
Alexandra,
Have a look at add1 and drop1.
Regards,
Jan
On 06/23/2011 07:32 PM, Alexandra Thorn wrote:
Here's a more general question following up on the specific question I
asked earlier:
Can anybody recommend an R command other than mle.aic() (from the wle
package) that will give back a ran
On 07/19/2012 05:50 PM, Hadley Wickham wrote:
On Thu, Jul 19, 2012 at 8:02 AM, Jan van der Laan wrote:
The following function is faster than your g and easier to read:
g2 <- function(dotot) {
v <- list()
for (i in seq_len(dotot)) {
v[[i]] <- FALSE
}
}
Except that you d
AM, Jan van der Laan wrote:
Johan,
Your 'list' and 'array doubling' code can be written much more efficient.
The following function is faster than your g and easier to read:
g2 <- function(dotot) {
v <- list()
for (i in seq_len(dotot)) {
v[[i]] <- FAL
oject.org
Subject: Re: [R] complexity of operations in R
Hadley et. al:
Indeed. And using a loop is a poor way to do it anyway.
v <- as.list(rep(FALSE,dotot))
is way faster.
-- Bert
On Thu, Jul 19, 2012 at 8:50 AM, Hadley Wickham wrote:
On Thu, Jul 19, 2012 at 8:02 AM, Jan van der Laan
ALSE)
}
return(v$get())
}
system.time(h3(1E5))
user system elapsed
22.846 0.536 23.407
system.time(h4(1E5))
user system elapsed
0.700 0.000 0.702
Jan
Johan Henriksson schreef:
On Thu, Jul 19, 2012 at 5:02 PM, Jan van der Laan wrote:
Johan,
Your 'list&#
Having had a quick look at the source code for read.table.ffdf, I
suspect that using 'NULL' in the colClasses argument is not allowed.
Could you try to see if you can use read.table.ffdf with specifying
the colClasses for all columns (thereby reading in all columns in the
file)? If that w
Looking at the source code for read.table.ffdf what seems to happen is
that when reading the first block of data by read.table (standard 1000
lines) the specified colClasses are used. In subsequent calls the
types of the columns of the ffdf object are used as colClasses. In
your case the
You probably have a character (which is converted to factor) or factor
column with a large number of distinct values. All the levels of a
factor are stored in memory in ff.
Jan
threshold schreef:
*..plus I get the following message after reading the whole set (all 7
columns):*
read.c
I come up with:
runs <- function(numbers) {
tmp <- diff(c(0, which(diff(numbers) <= 0), length(numbers)))
split(numbers, rep(seq_along(tmp), tmp))
}
Can't say it's elegant, but it seems to work
runs(c(1:3, 1:4))
$`1`
[1] 1 2 3
$`2`
[1] 1 2 3 4
runs(c(1,1,1))
$`1`
[1] 1
$`2`
[1]
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