You cannot obtain a predictable result by sending invalid time
representation data to strptime... you have to work with valid time
representations.
See sample approach below:
weekEnds <- function( DF ) {
d1_1 <- as.Date( sprintf( "%04d 1 1"
If you wish to use R, you need to at least understand its basic data
structures and functionality. Expecting that mimickry of code in special
packages will suffice is, I believe, an illusion. If you haven't already
done so, you should go through a basic R tutorial or two (there are many on
the web;
This would almost certainly fit better on the r-sig-mixed-models
list,rather than here. You are more likely to get authoritative responses
about this specialized statistical topic there.
Also -- these are **plain text** mailing lists. Please do not post in html.
Cheers,
Bert
Bert Gunter
"The t
Hello,
I would like to simulate nested data, where my mixed effects model fitted
to real data has the form:
y ~ time + (1 | site/subject)
I then take the hyper-parameters from this model to simulate fake data,
using this function:
create_fake <- function(J,K,L,HP,t){
I do not have your command of base r, Bert. That is a herculean effort! Here’s
what I spent my night putting together:
## Create search terms
## dput(st)
st <- structure(list(word1 = c("technique", "me", "me", "feel", "feel"
), word2 = c("olympic", "abused", "hurt", "hopeless", "alone"
), word3 =
I'm trying to select points randomly (without replacement) from a
SpatialPointsDataFrame (input object) with a minimum distance of 3,000
meters between them. I want to get random 50% of all points and create a
vector object with lines index as result. I tried to use sample() function
but I still di
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