R - Good programming practice

1. Instead of x[ind ,], use x[ind, , drop = FALSE]
   from here: R has a flaw in terms of how it behaves when you subscript a matrix and the new matrix has a dimension length of 1 for one (or more dimensions). For example, if a = array (0, dim = c( 1, 2, 4 )), then a[, , 1] is no longer a matrix but instead is a vector and dim(a[, , 1]) is NULL. This can cause all sorts of mysterious bugs. Sometimes adding drop=FALSE will prevent this unpleasant behavior. If b = matrix(0, 2, 2), dim( b[, 1 , drop = FALSE]) is c(2, 1) while dim( b[, 1] ) is NULL. drop = FALSE works great with 2-dimensional matrices, but with 3-dimensional matrices it doesn't work. If a = array (0, dim = c(1, 2, 4)), dim( a[, , 1, drop = FALSE] ) is c(1, 2, 1), instead of c(1, 2).
2. tricky because of NAs: For data frames (and vectors): Use subset(x, ...) instead of x [, \dots]
3. Use ’1:n’ only when you know that n is positive: Instead of 1:length(obj), use seq(along.with = obj)
4. Do not grow objects.
   

   Replace
   rmat <− NULL
   for ( i in  1:n ) {
   

   rmat <− rbind ( rmat , long.computation ( i , . . . . . ) )

   }
   with
   rmat <− matrix ( 0, n, k )
   for ( i in  1:n ) {
   

   rmat [i, ] <− long.computation ( i , . . . . . )

   }
   

5. Use with(, ......) and do not attach data frames
6. TRUE and FALSE, not ‘T’ and ‘F’ !
7. know the difference between ‘|’ vs ‘||’ and ‘&’ vs ‘&&’ and inside if ( .... ) almost always use ‘||’ and ‘&&’ !
8. use which.max(), . . . , findInterval()
9. use mat[i, j] <− if (A) A.expression  else  B.expression
   instead of
   if (A) mat[ i, j ] <− A.expression
   else   mat[ i, j ] <− B.expression
10.