Big O notation (for calculus, not computer science)

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Discussion Overview

The discussion revolves around the interpretation and application of big O notation, particularly in the context of calculus and random variables. Participants explore the implications of using big O versus little o notation and the conditions under which these notations apply, especially regarding limits and growth rates.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning

Main Points Raised

  • One participant seeks an intuitive interpretation of big O notation, questioning if f(x) = O(x^(-1/4)) implies that f(x) grows at the same rate as n^(-1/4) for large n.
  • Another participant argues that the definition of O notation requires a limit to be specified, suggesting that the initial question lacks clarity.
  • A correction is made regarding the use of O versus Op notation, with a participant asserting that the distinction does not significantly alter the question.
  • Some participants note that it is common practice to use O notation to imply behavior as x approaches infinity, although this may be seen as an abuse of notation.
  • There is a discussion about the implications of f = Op(n^(-1/4)), with one participant asserting that this does not necessarily mean f grows at the same rate as n^(-1/4) due to potential oscillatory behavior.
  • An example is provided where f(x) = Ax^(-1/4)cos(x^2) is O(x^(-1/4)), but its growth rate is influenced by oscillations, complicating the interpretation.

Areas of Agreement / Disagreement

Participants express differing views on the interpretation of big O notation and its application, particularly regarding limits and growth rates. There is no consensus on the implications of using O versus Op notation or the conditions under which these notations apply.

Contextual Notes

Participants highlight the need for clarity regarding the limits involved in big O notation and the potential for oscillatory behavior in functions that may affect their growth rates.

kungal
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I understand the formal definition for big O notation but is there an intuitive interpretation?. For example, if

Code:
f(x) = O(x[SUP]-1/4[/SUP])

is it reasonable to say that for large n f(x) grows at the same rate as
Code:
n[SUP]-1/4[/SUP]
?

Thanks in advance
 
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Your first line is meaningless.
An O-notation requires a limit to which the independent variable is supposed to go.
 
The O's should actually be Op's (my mistake) and x is a set of random variables. I don't think this changes the nature of the question drastically.

Note that the result f(x) = Op(x-1/4) is quite common so it can't be a meaningless statement.
 
kungal said:
The O's should actually be Op's (my mistake) and x is a set of random variables. I don't think this changes the nature of the question drastically.

Note that the result f(x) = Op(x-1/4) is quite common so it can't be a meaningless statement.

Yes it is.

Is it meant that f(x) is O(x^(-1/4) ) as x goes to zero, or as x goes to, say, infinity?
That is two entirely different situations, and needs, therefore, to be specified.
Hence, the meaninglessness of your first line.
 
I hate to disagree with Arildno but it is common practice (though perhaps "abuse of notation") to use just O(f(x)) to mean "as x goes to infinity".
 
HallsofIvy said:
I hate to disagree with Arildno but it is common practice (though perhaps "abuse of notation") to use just O(f(x)) to mean "as x goes to infinity".
Well, if that is the general default notation, I'll make a note of that.

In my own applied maths books, they dutifully make explicit what limiting operation we are speaking about
 
I'm glad we've cleared that up but is it reasonable to say that
if f = Op(n-1/4) then for large n f grows at the same rate as n-1/4?
 
kungal said:
I'm glad we've cleared that up but is it reasonable to say that
if f = Op(n-1/4) then for large n f grows at the same rate as n-1/4?

Not at all.

f might, for example, become more and more strongly oscillatory as x goes to infinty, even though f's magnitude will be bounded by some constant multiplied by x^(-1/4).

For example, let
[tex]f(x)=Ax^{-\frac{1}{4}}\cos(x^{2})[/tex]

This f is definitely O(x^(-1/4)), but its rate of growth will, be:
[tex]\frac{df}{dx}\to{-2A}x^{\frac{3}{4}}\sin(x^{2}), x\to\infty[/tex]
 
Thanks
 
  • #10
Well, O's should actually be Op's (my mistake) and x is a set of random variables.
 

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