This board says the easiest way to turn off line-wrapping is to use ODS output to HTML:     Google Forum about SAS   Then this SAS Note says, to do that in HTML, you would need to use a template code they provide:       Usage Note 23373     ... View more

It is an interesting idea about the mode. I think you forgot to attach the link. ... View more

I agree, it is not as straight-forward to do array slices, like Python list slices. ... View more

Here is a clarification about equi leaders:   Keeping in mind that a leader, simply put, is the most popular element in an array,   if we have an array 434442, the overall leader is 4. The questions is, how many times will we come across equi leaders in this array?   To find out, we split the array sequentially like this:   1) 4 (leader = 4)  and 34442 (leader = 4) ----------> bingo! first instance of an equi leader   2) 43 (leader = -1, i.e., not there) and 4442 (leader = 4)   3)  434 (leader = 4) and 442 (leader = 4)  ---------> bingo! second instance of an equi leader   4) 4344 (leader = 4) and 42 (leader = -1)   5) 11223 (leader = -1) and 3 (leader = 3)   Therefore, the count of equi leaders is 2.   Reference   Codility Lesson 8: Leaders ... View more

1) For example, if one variable stores array sequences, like 123456, and the other variable - their leaders. This 123456 array will not have a leader, so the leader variable should default to (-1). 2) I will put this answer in a separate response. ... View more

Can 'to: ' be a list of emails?    and where is he doing that: Note: When using SAS to email graphics output, you must first set the EMAILSYS system option to SMTP and the EMAILHOST system option to the name of the SMTP email server at your site.   Reference   Use SAS to send an email with a graph ... View more

There are probably variables in the model with data that is similar to other variables, producing multicollinearity. CSIndex values are monotonous or missing.   ranking - sorting numerical or ordinal variables in ascending order    multicollinearity - when one predictor variable in multiple regression model can be linearly predicted from the others   problem of multicollinearity - the coefficient estimates of the multiple regression may change erratically in response to small changes in the model or the data   some causes of multicollienarity:   inclusion of a variable which is computed from other variables in the data set; the repetition of the same kind of variable.    scaling - normalizing data to a common range   See also,   The Panel procedure: Unbalanced data ... View more