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
> By the way, since the tcrossprod function in the Matrix package is so fast,
> the Euclidean distance can be computed very fast:
Indeed.
> euc_dist <- function(m) {mtm <- Matrix::tcrossprod(m); sq <- rowSums(m*m);
> sqrt(outer(sq,sq,"+") - 2*mtm)}
There are two reasons why I didn't use this
Dear Jens,
multiple people have given you multiple reasons as to why your request
cannot be implemented for basic logical reasons. You also got a workaround
for the special case where all factors have all the same levels in exactly
the same order.
If you believe it's possible to implement this in
Defending the status quo misses the point that R *could* handle ordinal data
with a fixed set of levels but actually *does not*. Although it would be
useful. Even if this does not imply to handle any possible straw-man
situations. Having data-types for nominal, ordinal, and interval-scale data i
Hi, Duncan
i have forwarded this thread to Nathan, who promised to look into it.
Andrie
On 17 Jun 2017 17:26, "Duncan Murdoch" wrote:
> On 17/06/2017 9:13 AM, Ben Marwick wrote:
>
>> Hi Duncan,
>>
>> Thanks for your reply. Yes, it does seem to be specific to the CTYPE
>> setting to Chinese on
