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The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.
But why on earth?!
Assuming a linear complete model of the form:
z = a + bx + cy + ε.
Where z is supposed to be dependent, x and y are independent and ε is the error term.
Now we drop y to check…Continue
The positive reactions on my last post: “Different kinds of loops in R” lead me to compare some different versions of loops in R, RCPP (C++ integration of R). To see a bigger picture, I apply the Python for-loop additionally. The comparison focuses on the runtime for non-costly tasks with different numbers of iterations. For comparison purpose I create vectors in the form of (R syntax):
Vector <- 1:k
k = (1.000, 100.000, 1.000.000)
The task is to…Continue
Normally, it is better to avoid loops in R. But for highly individual tasks a vectorization is not always possible. Hence, a loop is needed – if the problem is decomposable.
Which different kinds of loops exist in R and which one to use in which situation?
In each programming language, for- and while-loops (sometimes until-loops) exist. These loops are sequential and not that fast – in R.