Function of 2 variables, max/min test, D=0 and linear dependence

In summary: The rank one nature means that all ##3## partials I could compute with it are linearly dependent, in particular ##x_1^2 = (-x_2)^2##, the first and second partials are linearly dependent.Going back to your original problem, if ##f(x,y) = (x + y)^2##, then the first and second partials are linearly dependent, and the Hessian is rank one. (you get same hessian as above but with ##x,y## instead of ##x1,x2##)In summary, a critical point for a function f(x,y) is given by f_x=0 and f_y=0 simultaneously. The test for identifying if
  • #1
binbagsss
1,254
11
##f(x,y)##

a critical point is given by ##f_x=0## and ##f_y=0## simultaneously.

the test is:

##D=f_{xx}f_{yy}-(f_{xy})^2 ##

if ##D >0 ## and ##f_{xx} <0 ## it is a max
if ##D >0 ## and ##f_{xx} >0 ## it is a min
##D >0 ## is is a saddle
if ##D =0 ## it is inconclusive, and ##f_x## and ##f_y## are not linear independent.

I'm stuck on the ##D=0## comment re linear independence. So is this saying that ##x## and ##y## are not linear indepedent?

So if i take an arbitary function ##f(x,y) ## and ##y=h(x)##, h some linear function, then I should get ##D=0## or not?
 
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  • #2
It is saying that the two first partials are linearly dependent, not that x and y are linearly dependent.
 
  • #3
Mark44 said:
It is saying that the two first partials are linearly dependent, not that x and y are linearly dependent.

What is characteristic of a function whose partials are linearly dependent?
 
  • #4
binbagsss said:
What is characteristic of a function whose partials are linearly dependent?
If two functions (partials in this case) are linearly dependent, then each will be a constant multiple of the other.
 
  • #5
Mark44 said:
If two functions (partials in this case) are linearly dependent, then each will be a constant multiple of the other.
yup, so if i have a ##f(x,y)## function all term must be a multiple of ##(xy)^n## , ##n \in R## or if it contains terms solely of ##x## or ##y## they must be of at most the power of ##2##? (To conclude the partials ##f_x## and ##f_y## are linear dependent, not higher partials)?

edit: re second comment is incorrect, but would yield ##D=0## without implying that ##f_x## and ##f_y## are linearly independent? so in OP comment only holds for higher powers? or a function without sole terrms of x or y if the power is lower
 
  • #6
binbagsss said:
yup, so if i have a ##f(x,y)## function all term must be a multiple of ##(xy)^n## , ##n \in R## or if it contains terms solely of ##x## or ##y## they must be of at most the power of ##2##? (To conclude the partials ##f_x## and ##f_y## are linear dependent, not higher partials)?
I haven't worked out an example. You want a function f(x, y) such that fx = fy = 0, and for which the discriminant D = 0.
 
  • #7
Mark44 said:
I haven't worked out an example. You want a function f(x, y) such that fx = fy = 0, and for which the discriminant D = 0.
apologies edited post since above
 
  • #8
binbagsss said:
##f(x,y)##

a critical point is given by...
##D >0 ## is is a saddle

this is a typo and should say less than zero.
binbagsss said:
if ##D =0 ## it is inconclusive, and ##f_x## and ##f_y## are not linear independent.

I'm stuck on the ##D=0## comment re linear independence. So is this saying that ##x## and ##y## are not linear indepedent?

This is a lot easier in my view if you know bits about linear algebra. Do you know what a Hessian is? How about a quadratic form?

consider the 2 variable function (I used ##x_1, x_2## instead of ##x,y##:

edit: (due to some domain subtleties, the below is a better example than the prior function I mentioned)

##f(x_1,x_2) = (x_1 + x_2)^2 = x_1^2 + x_2^2 + 2x_1 x_2##

The Hessian is given by
##
\mathbf H = \begin{bmatrix}
2 & 2\\
2 & 2
\end{bmatrix} = 2 \big(\mathbf 1 \mathbf 1^T\big)##

This is a rank one matrix and hence has determinant of zero. (Equivalently compute the determinant directly and see ##2*2 - 2*2 = 0## )
 
Last edited:

1. What is the function of 2 variables?

The function of 2 variables is a mathematical expression that maps a set of inputs from 2 independent variables to a corresponding set of outputs. It is represented in the form of f(x,y) where x and y are the two variables.

2. What is the max/min test for a function of 2 variables?

The max/min test for a function of 2 variables is a method used to determine the maximum and minimum values of the function. It involves finding critical points where the partial derivatives of the function with respect to both variables are equal to zero, and then evaluating the function at these points to determine the maxima and minima.

3. What does D=0 mean in terms of a function of 2 variables?

D=0 refers to the determinant of the Hessian matrix of a function of 2 variables. If D=0, it indicates that the function has a saddle point or a point of inflection, and further analysis is needed to determine the nature of the critical point.

4. How do you test for linear dependence in a function of 2 variables?

To test for linear dependence in a function of 2 variables, we can use the method of elimination. If the partial derivatives of the function with respect to both variables are equal to a constant multiple of each other, then the function is linearly dependent. If they are not, then the function is linearly independent.

5. How are the max/min values affected by linear dependence in a function of 2 variables?

If a function of 2 variables is linearly dependent, it means that there is no maximum or minimum value for the function. This is because the function is not truly dependent on both variables, and therefore does not have a distinct maximum or minimum point.

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