Magic number 2.220446e-16

If you have seen one of my old posts: Interesting unequal math equation, you would know there is an accuracy problem in R. And I give an explanation in that post: “Most float number has no exact representation in binary format, just approximation”.  Here I decide to dig a litter bit deeper.

Let’s look at some examples first.

> 1.37+0.12-1.49
[1] 2.220446e-16
> 1.38+0.12-1.5
[1] 0
> 1.39+0.12-1.51
[1] -2.220446e-16

See, notice the number there, 2.220446e-16. Do you think it’s just a coincidence ?
Of course not.

Thanks to Google, I find a detailed explanation about this problem.

Real numbers in R are stored in double precision, which means that 53 bit floating point arithmetic in base 2 is used. This may be seen from

> 1 + 2^-52 == 1
[1] FALSE
> 1 + 2^-53 == 1
[1] TRUE

The number 1 + 2^-52 with a 53 bit mantissa is exactly representable, while 1 + 2^-53 with 54 bit mantissa is rounded to 1. The smallest difference between two consecutive representable numbers in the interval [1 , 2) is about 2.220446e-16 which exactly equals to 2^-52.

Double precision is the standard for numerical calculations, where speed is required. This cannot represent irrational numbers and rational numbers, whose denominator is not a power of 2. In particular, numbers with a finite number of decimal digits need not have a finite expansion as a binary number. This is the reason for the following

> 0.1 + 0.2 - 0.3
[1] 5.551115e-17

Similar effects may be demonstrated using decimal numbers. The reason for the above is similar to the reason, why 2/3 – 1/3 – 1/3 is not 0, if 1/3 and 2/3 are rounded to a finite number of decimal digits. With 5 digits, we get 0.66667 – 0.33333 – 0.33333 = 0.00001.

The fact that numbers like 0.1 are not represented exactly does not mean that we cannot get correct result, at least in simple cases, if the calculations are done with care. In particular, for correcting errors of addition and subtraction of fractional decimal numbers, the functions round() and signif() may be used.

 

 Reference:

http://rwiki.sciviews.org/doku.php?id=misc:r_accuracy

http://stackoverflow.com/questions/6970705/why-cant-i-get-a-p-value-smaller-than-2-2e-16-in-r

Invisible Character Alt-255

The text aligning and positioning in SAS output is really important if you want your report looks good. I usually use space to aligning text in titles, footnotes and columns, etc. However, SAS have its own rule to handle the blanks, especially the leading or trailing blanks, so sometimes the space cannot do what you want.

Here I’m introducing a new simple and elegant approach: using Alt-255. It looks like a blank space in the program code and SAS output but is processed and printed by many programs as a valid text character.

Now, how? First of all, remember you need to use a numeric keypad for typing the magic number 255.

You should follow the following steps to create an invisible Character.

1. Press and hold the “Alt” key and while holding it, type digit keys 255 from numeric keypad.
2. Release the “Alt” key and after releasing the cursor will moves to the next position so you will know that an invisible character has been inserted.

Actually, we can use Alt-N to enter any letter and a lot of graphical symbols. There is a nice place where you can check all Alt-N characters (http://www.alt-codes.net/). Alt-255 is of special interest just because it is invisible.

See the example below:

data test;
  input fname $;
* The blank before Alan is Alt-255, before Andy is space;
datalines;
Joe
 Alan
 Andy
;
run;

proc print data=test;
run;

And the result:

1 Joe
2  Alan
3 Andy