Oh, there are ways, but the constraining issue here is moving data (memory
bandwidth), and data table is probably already the fastest mechanism for doing
that. If you have a computer with four or more real cores you can try setting
up a subset of the columns in each task and cbind the results af
Try this code:
# Standard deviations and correlation
sig_x <- 1
sig_y <- 2
rho_xy <- 0.7
# Covariance between X and Y
sig_xy <- rho_xy * sig_x *sig_y
# Covariance matrix
Sigma_xy <- matrix(c(sig_x ^ 2, sig_xy, sig_xy, sig_y ^ 2), nrow = 2,
ncol = 2)
# Load the mvtnorm package
library("mvtnor
You have 10^7 columns? That process is bound to be slow.
On April 13, 2018 5:31:32 PM PDT, Jack Arnestad wrote:
>I have a data.table with dimensions 100 by 10^7.
>
>When I do
>
>trainIndex <-
> caret::createDataPartition(
>df$status,
>p = .9,
>list = FALSE,
>
I have a data.table with dimensions 100 by 10^7.
When I do
trainIndex <-
caret::createDataPartition(
df$status,
p = .9,
list = FALSE,
times = 1
)
outerTrain <- df[trainIndex]
outerTest <- df[-trainIndex]
Subsetting the rows of df takes ove
Suppose that (e.g.) xyplot() returns an object "xxx" with (say) 3 pages.
I would like to extract/plot (print) just one of these pages, e.g.
page 2.
Here's a toy example:
x <- rep(seq(0,1,length=11),12)
set.seed(42)
y <- rnorm(3*44)
a <- rep(letters[1:12],each=11)
dta <- data.frame(x=x,y=y
Dear R-experts,
I am trying to do cross-validation for different models using the cvTools
package.
I can't get the CV for the "FastTau" and "hbrfit". I guess I have to write my
own functions at least for hbrfit. What is going wrong with FastTau ?
Here below the reproducible example. It is a si
> On Apr 13, 2018, at 10:01 AM, WRAY NICHOLAS via R-help
> wrote:
>
> Hello R folk
>
> I have an xpt file which I have been trying to open into R in R studio
>
> On the net I found guidance which says that I need packages Hmisc and
> SASxport which I have successfully loaded.
>
> I had also
R-Help
I'm working in my first large database (53,098,492,383 records). When I
select the db via something like
Library(SparkR)
mydata <- sql("SELECT * FROM ")
is "mydata" a SparkDataFrame, and do I work with SparkDataFrames like I
would regular df (per say); because I can't image I
Longitudinal and Multilevel Data in R and Stan
ICPSR short course: May 28 to June 1, 2018
May 28: Introduction to R by John Fox
May 29 to June 1: Longitudinal and Multilevel Data in R and Stan by Georges
Monette
Sponsored and organized by ICPSR, University of Michigan and
held at York University
Hello R folk
I have an xpt file which I have been trying to open into R in R studio
On the net I found guidance which says that I need packages Hmisc and SASxport
which I have successfully loaded.
I had also found some code which says that this would allow me to read the xpt
file into R:
libr
You can record the time to evaluate each line by wrapping each line in a
call to system.time(). E.g.,
expressions <- quote({
# paste your commands here, or put them into a file and use exprs <-
parse("thatFile")
d.dir <- '/Users/darshanpandya/xx'
FNAME <- 'my_data.csv'
d.input <- fre
Hello,
Writing to seek help in regard to some unexpected performance anomaly i am
observing in using tsoutlers:tso on the mac vs on an AWS cloud server..
I am running the following code with very small dataset of about 208
records.
d.dir <- '/Users/darshanpandya/xx'
FNAME <- 'my_data.csv'
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