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The code is like this
x <- 1:5
x[NA]
Why does it produce 5 NAs?
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However, the cross product is closely connected to the determinant, which is evident if you look at the formulas for each. As someone else said, the magnitude of the cross product is equal to this area. This is similar to how the dot product gives the magnitude of the projection of vector a unto vector b.
However, the cross product is closely connected to the determinant, which is evident if you look at the formulas for each. As someone else said, the magnitude of the cross product is equal to this area.
No, that's the determinant. However, the cross product is closely connected to the determinant, which is evident if you look at the formulas for each. As someone else said, the magnitude of the cross product is equal to this area.
For instance when you make a table of values and say there are zero of that cell you need to hold that that cell made from a string in a vector has no values. it would not be a appropriate to have x[0]==0 as it's not the numeric value of zero but the absence of any value.
The answer to this question has two sides:
How is NA interpreted when indexing matrices?
In one of the links provided by @alexis_laz, I found a very well structured explanation of how TRUE, FALSE and NA are interpreted when indexing matrices:
Logicalindices tellRwhich elements to include or exclude.You have three options:
TRUE,FALSEandNAThey serve to indicate whether or not the index represented in that position should be included. In other words:
TRUE == "Include the elment at this index" FALSE == "Do not include the element at this index" NA == "Return NA instead of this index" # loosely speakingFor example:
x <- 1:6 x[ c(TRUE, FALSE, TRUE, NA, TRUE, FALSE)] # [1] 1 3 NA 5
An important detail is that the default storage mode for an isolated NA value is logical (try typeof(NA)). You can choose the storage mode of the NA by using NA_integer_, NA_real_ (for double), NA_complex_ or NA_character_.
Why 5 NA and not just 1?
When the length of the indices is smaller than the length of vector x, the indexing will start over to also index the values in x that have not been indexed yet. In other words, R will automatically "recycle" the indices:
(...) However, standard recycling rules apply. So in the previous example, if we drop the last
FALSE, the index vector is recycled, the first element of the index isTRUE, and hence the 6th element ofxis now includedx <- 1:6 x[c(TRUE, FALSE, TRUE, NA, TRUE)] # [1] 1 3 NA 5 6
Recall the detail about the storage mode from the previous section. If you type x[NA_integer_], then you will find a different result.
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