Hello,
Below is my code:
> A <- matrix(rnorm(10*3),ncol=3)
> b <- runif(10)
> reg <- lm(b ~ A)
> A1 <- matrix(rnorm(5*3),ncol=3)
> A1 <- as.data.frame(A1)
> b1 <- predict(reg,A1)
Warning message:
'newdata' had 5 rows but variables found have 10 rows
And instead of being an array of length 5, b1
I think that even though some Microsoft employees may have good intentions
Microsoft as a company can not be trusted. There will be always a danger that
they will try to create their own version of R which works only on Windows and
that will become increasingly divergent from "other" R. We witne
I tried this on a Linux (Ubuntu) server invoking R from the command line and
the result was the same, except that I could kill the R session from another
terminal window.
From: Rui Barradas
To: Chris Triggs ; "r-devel@r-project.org"
Cc: Thomas Lumley
Sent: Thursday, 17 August 2017,
Hi Stefan,
You are right about the possible loss of accuracy computing the Euclidean
distance the way I did. In some cases you probably even can get a negative
value to compute a square root (so I am making all negative numbers 0). To do
what I did one must know that it is all right in their cas
of magnitude faster than dist).
From: Stefan Evert
To: Moshe Olshansky
Cc: R-devel Mailing List
Sent: Sunday, 18 June 2017, 2:33
Subject: Re: [Rd] dist function in R is very slow
> On 17 Jun 2017, at 08:47, Moshe Olshansky via R-devel
> wrote:
>
> I am visualising h
Dear R developers,
I am visualising high dimensional genomic data and for this purpose I need to
compute pairwise distances between many points in a high-dimensional space (say
I have a matrix of 5,000 rows and 20,000 columns, so the result is a
5,000x5,000 matrix or it's upper diagonal).Computi
