I wanted to compress a raw vector into another raw vector. This problem
is solved using memCompress. However before discovering this function, I
first tried to get this working using gzcon. From the documentation it
seems that this should be possible:
> Compressed output will contain e
On 1/14/25 10:07, akshay kulkarni wrote:
dear Ivan,
THe present problem had been encountered by me also about 1
and a half years ago. You had solved the issue then. Can't we search this mail
list according to some keywords? It helps people with problems already solved
in t
On 10/11/24 11:56, Rui Barradas wrote:
Hello,
A way to have different time zones is to store t1 and t2 in list,
which are vectors. Just not atomic vectors.
I think it complicates what should be simple, but here it is.
# create two lists
t1 <- lapply(c("2024-01-01 12:30", "2024-01-01 12:30
Thanks,
On 10/11/24 09:10, Ivan Krylov wrote:
В Thu, 10 Oct 2024 17:16:52 +0200
Jan van der Laan пишет:
This is where it is unclear to me what the purpose is of the `zone`
element of the POSIXlt object. It does allow for registering a time
zone per element. It just seems to be ignored.
I
T and it would
be fine to convert them to a single time zone if that is what it takes
to work with them in R. So, I guess, I could split the vector in two,
convert local time to GMT and combine them again (respecting the
original order).
Jan
On October 10, 2024 6:46:19 AM PDT, Jan van
It is not completely clear to me how time zones work with POSIXlt
objects. For POSIXct, I can understand what happens: time is always
stored in GMT, the `tzone` attribute only affects how the times are
displayed. All computations etc. are done in GMT.
POSIXlt objects have both a `tzone` att
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
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
B" = "grey",
"C" = "green"),
labels = c("Deteriorated",
"No change",
"Improved")) +
scale_fill_manual(name = "Change"
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)
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
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
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
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
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
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
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:
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
(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
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
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
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
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
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
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/
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
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
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
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,
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)
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
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:
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
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
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
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,
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.
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
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
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:
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
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
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
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
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
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
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
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
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
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 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
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
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
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
$`2`
[1]
You probably have a character (which is converted to factor) or factor
column with a large number of distinct values. All the levels of a
factor are stored in memory in ff.
Jan
threshold schreef:
*..plus I get the following message after reading the whole set (all 7
columns):*
read.c
Looking at the source code for read.table.ffdf what seems to happen is
that when reading the first block of data by read.table (standard 1000
lines) the specified colClasses are used. In subsequent calls the
types of the columns of the ffdf object are used as colClasses. In
your case the
Having had a quick look at the source code for read.table.ffdf, I
suspect that using 'NULL' in the colClasses argument is not allowed.
Could you try to see if you can use read.table.ffdf with specifying
the colClasses for all columns (thereby reading in all columns in the
file)? If that w
ALSE)
}
return(v$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&#
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
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
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
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
I don't know if any R-packages exist that can do this, but you could
install imagemagick (http://www.imagemagick.org), which provides
command line tools for image manipulation and conversion, and call
these from R using system. Something like:
system("convert yourimage.ppm yourimage.bmp")
using reshape:
library(reshape)
m <- melt(my.df, id.var="pathway", na.rm=T)
cast(m, pathway~variable, sum, fill=NA)
Jan
On 05/07/2012 12:30 PM, Karl Brand wrote:
Dimitris, Petra,
Thank you! aggregate() is my lesson for today, not melt() | cast()
Really appreciate the super fast help,
Karl
Perhaps you could contact the persons that supplied/created the file and
ask them what the format of the file exactly is. That is probably the
safest thing to do.
If you are sure that the lines containing only whitespace are
meaningless, then you could alter the previous code to make a copy
OK, not all, but most lines have the same length. Perhaps you could
write the lines with a different line size to a separate file to have
a closer look at those lines. Modifying the previous code (again not
tested):
con <- file("dataset.txt", "rt")
out <- file("strangelines.txt", "wt")
#
or
identical(vec1, vec2) && identical(vec2, vec3)
Jan
Petr Savicky schreef:
On Fri, May 04, 2012 at 12:53:12AM -0700, aaurouss wrote:
Hello,
I'm writing a piece of code where I need to compare multiple same length
vectors.
I've gone through the basic functions like identical() or all(),
read.delim calls read.table so any differences between the two are
caused by differences in the default values of some of the parameters.
Take a look at the help file ?read.table
read.table uses white space as separator; read.delim tabs
read.table uses " and ' as quotes; read.delim just "
e
read.table imports the company name "GREAT FALLS GAS CO" as four
separate columns. I think that needs to be one column. I can imagine
that further one in your file you will have another company name that
does not consist of four words which would cause the error you
observed. From your ou
The 'normal' way of doing that with ff is to first convert your csv
file completely to a
ffdf object (which stores its data on disk so shouldn't give any
memory problems). You
can then use the chunk routine (see ?chunk) to divide your data in the
required chunks.
Untested so may contain err
Your question is not completely clear. read.csv.ffdf automatically
reads in the data in chunks. You don´t have to do anything for that. You
can specify the size of the chunks using the next.rows option.
Jan
On 03/24/2012 09:29 PM, Mav wrote:
Hello!
A question about reading large CSV files
What you could try to do is skip the first 5 lines. After that the file
seems to be 'normal'. With read.table.ffdf you could try something like
# open a connection to the file
con <- file('yourfile', 'rt')
# skip first 5 lines
tmp <- readLines(con, n=5)
# read the remainder using read.table.ff
Marianna,
You can use merge for that (or match). Using merge:
MyData <- data.frame(
V1=c("red-j", "red-j", "red-j", "red-j", "red-j", "red-j"),
V4=c(10.5032, 9.3749, 10.2167, 10.8200, 9.2831, 8.2838),
redNew=c("appearance blood-n", "appearance ground-n", "appearance
sea-n", "appeara
You could also have a look at the LaF package which is written to
handle large text files:
http://cran.r-project.org/web/packages/LaF/index.html
Under the vignettes you'll find a manual.
Note: LaF does not help you to fit 9GB of data in 4GB of memory, but
it could help you reading your fi
Step by step:
1. Create a new document in Open/LibreOffice
2. Copy/paste the following text into the document (as an example)
<>=
cat("Hello, world")
@
2. Save the file (e.g. "hello.odt")
3. Start R (if not already) shouldn't matter if its plain R/RStudio
4. Change working directory to the fol
The suggestion below gives you week numbers with week 1 being the week
containing the first monday of the year and weeks going from monday to
sunday. There are other conventions. The ISO convention is that week 1
is the first week containing at least 4 days in the new year (week 1
of 2012
I don't know if this completely solves your problem, but here are some
arguments to read.table/read.delim you might try:
row.names=FALSE
fill=TRUE
The details section also suggests using the colClasses argument as the
number of columns is determined from the first 5 rows which may not be
very much for the solution given. Still I am having one
more question.
I want both the graphs in single pdf and the legend should contain
ACTTRT of individual REFID (Only two lines in legend)
Can you solve it?
Devarayalu
-Original Message-
From: Jan van der Laan [mailto:rh
reply. But...
Sorry still I am not getting by using print() with the following
modified code. I am also attaching the raw datafile.
par(mfrow=c(1,3))
#qplot(TIME1, BASCHGA, data=Orange1, geom= c("point", "line"),
colour= ACTTRT)
unique(Orange1$REFID) -> refid
for
Devarayalu,
This is FAQ 7.22:
http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-do-lattice_002ftrellis-graphics-not-work_003f
use print(qplot())
Regards,
Jan
Sri krishna Devarayalu Balanagu schreef:
Hi All,
Can you please help me, why this code in not generating line chart?
librar
What I did in the past (not with R scripts) is to start my jobs using
at (start the job at a specified time e.g. now) or batch (start the
job when the cpu drops below ?%)
at now "R CMD BATCH yourscript.R"
or
batch "R CMD BATCH yourscript.R"
something like that, you'll have to look at the m
n the future.
Thanks again!
Emma
- Original Message -
From: Jan van der Laan
To: "r-help@r-project.org"
Cc: Emma Thomas
Sent: Wednesday, December 14, 2011 6:18 AM
Subject: Re: [R] Generating input population for microsimulation
Emma,
If, as you say, each unit is the sa
Emma,
If, as you say, each unit is the same you can just repeat the units to
obtain the required number of units. For example,
unit_size <- 10
n_units <- 10
unit_id <- rep(1:n_units, each=unit_size)
pid <- rep(1:unit_size, n_units)
senior <- ifelse(pid <= 2, 1, 0)
pop <- d
Raphael,
This looks like fixed width format which you can read with read.fwf.
In fixed width format the columns are not separated by white space (or
other characters), but are identified by the positition in the file.
So in your file, for example the first field looks to contained in the
I assume you use a command window to build your packages. One possible
solution might be to leave out the path variables set by Rtools from
your global path and to create a separate shortcut to cmd for building
r-packages where you set your path as needed by R CMD build/check
Something like
Yet another solution. This time using the LaF package:
library(LaF)
d<-c(1,4,7,8)
P1 <- laf_open_csv("M1.csv", column_types=rep("double", 10), skip=1)
P2 <- laf_open_csv("M2.csv", column_types=rep("double", 10), skip=1)
for (i in d) {
M<-data.frame(P1[, i],P2[, i])
}
(The skip=1 is needed as l
The LaF package provides methods for fast access to large ASCII files.
Currently the following file formats are supported:
* comma separated format (csv) and other separated formats and
* fixed width format.
It is assumed that the files are too large to fit into memory, although
the package ca
plyr isn't necessary in this case. You can use the following:
cols <- sapply(df, is.numeric)
df[, cols] <- pct(df[,cols])
round (and therefore pct) accepts a data.frame and returns a
data.frame with the same dimensions. If that hadn't been the case
colwise might have been of help:
librar
George,
Perhaps the site of the RISQ project (Representativity indicators for
Survey Quality) might be of use: http://www.risq-project.eu/ . They
also provide R-code to calculate their indicators.
HTH,
Jan
Quoting ghe...@mathnmaps.com:
An organization has asked me to comment on the val
Quoting Uwe Ligges :
I don't agree that it's overkill -- you get to sidestep the whole `R
CMD SHLIB ...` and `dyn.load` dance this way while you experiment with
C(++) code 'live" using the inline package.
You need two additional packages now where you have to rely on the fact
those are avai
An obvious reason might be that your second argument should be a
pointer to int.
As others have mentioned, you might want to have a look at Rccp and/or
inline. The documentation is good and I find it much easier to work
with.
For example, your example could be written as:
library(Rcpp)
l
You can with the routines in the memisc library. You can open a file
using spss.system.file and then import a subset using subset. Look in
the help pages of spss.system.file for examples.
HTH
Jan
On 09/25/2011 11:56 PM, sassorauk wrote:
Is it possible to import only certain variables from a
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
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$append<- append
to the function. And even then there will be a problem with the
headers that are repeated
when appending.
An easier solution is to use write.table dire
Michael,
You example doesn't seem to work. Append isn't passed on to the
write.table call. You will need to add a
Call$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
(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
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
},
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
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'
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