Trying to Prove that Given Function is a Metric

In summary, the conversation discusses the attempt to prove that ##d_1\left({x,y}\right)=\max\{\left|{x_j-y_j}\right|:j=1,2,...,k\}## is a metric. The first part of the proof is straightforward, showing that ##d_1\left({x,y}\right) \geq 0## and ##d_1\left({x,y}\right) = d_1\left({y,x}\right)##. The difficulty lies in proving the triangle inequality, specifically how to connect it to the previous steps. The conversation hints at using a triangle inequality for the max, and also mentions the standard distance function in ##
  • #1
Bennigan88
38
0
Hello! I'm trying to prove that ##d_1\left({x,y}\right)=\max\{\left|{x_j-y_j}\right|:j=1,2,...,k\}## is a metric. I know that since ##d_1\left({x,y}\right) = \left|{x_j-y_j}\right|## for some ##j## that ##d_1\left({x,y}\right) \geq 0## and since ##\left|{x_j-y_j}\right| = \left|{y_j-x_j}\right|## that ##d_1\left({x,y}\right) = d_1\left({y,x}\right)##. Also, ## \left|{x_j-x_j}\right| = 0## for all ##j## thus ##d_1\left({x,x}\right) = 0##. The part that is giving me trouble is proving that ##d_1\left({x,y}\right) \leq d_1\left({x,z}\right) + d_1\left({z,y}\right)##. Any hints or tips? No spoilers please! Here are some things that I've shown so far, but I'm not seeing the connection between any of these and what I need.

Since ##dist\left({x,y}\right) \leq \sqrt{k}\cdot\max\{\left|{x_j-y_j}\right|:j=1,2,...k\}## where ##dist\left({x,y}\right)## is the standard distance function between points in ##\mathbb{R}^{k}##, I have ##dist\left({x,y}\right) \leq \sqrt{k}\cdot d_1\left({x,y}\right)##. I was thinking of trying to involve the reverse triangle inequality since that sometimes is the missing link for proofs that I'm stumped on, but the thing that messes me up is that the dimension in which lays the longest distance ##\left|{x_j-y_j}\right|## that is, the value of index ##j## could be different for the three pairs of points. I also know that ##d_1\left({x,y}\right) \leq dist\left({x,y}\right)## as the distance between two points in a single dimension can at most be the same as the distance between the points in the space. Are there any theorems or definitions that I'm missing? Thanks!
 
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  • #2
A triangle inequality for the max would be useful here.

Additional hint:
If you give it some thought you will hopefully see that
[tex]\max_i (a_i + b_i) \le \left(\max_i a_i \right) + \left(\max_i b_i\right)[/tex]
 
  • #3
CompuChip said:
A triangle inequality for the max would be useful here.

Additional hint:
If you give it some thought you will hopefully see that
[tex]\max_i (a_i + b_i) \le \left(\max_i a_i \right) + \left(\max_i b_i\right)[/tex]
I don't think I understand your notation :/
 
  • #4
Sorry, I am lazy when it comes to notation.
[tex]\max_i a_i[/tex]
is shorthand for
[tex]\max_{i = 1}^k a_i[/tex]
which in turn corresponds to your
[tex]\max \{ a_i \mid i = 1, \ldots k \}[/tex]

By the way, I assumed that k is the dimension of your space, i.e. you are trying to show that it's a metric on [itex]\mathbb{R}^k[/itex], and that xi is the i-th component of the vector x. If that is wrong, please let me know :)
 

Related to Trying to Prove that Given Function is a Metric

1. What is a metric function and why is it important?

A metric function is a mathematical function that measures the distance between two points in a space. It is important because it allows us to quantify the concept of distance and is a fundamental tool in many areas of mathematics, such as topology and analysis.

2. How do I prove that a given function is a metric?

To prove that a given function is a metric, you must show that it satisfies the three properties of a metric: non-negativity, symmetry, and the triangle inequality. This can be done by plugging in different values for the variables and showing that the function always produces valid results.

3. Can a metric function be defined for any type of space?

Yes, a metric function can be defined for any type of space, including finite and infinite dimensions. However, the specific form of the metric function may vary depending on the properties of the space.

4. Are there any common mistakes to avoid when trying to prove a given function is a metric?

One common mistake is assuming that a function is a metric based on intuition or previous knowledge, without actually proving it satisfies the three properties. Another mistake is forgetting to check for non-negativity, which is a crucial property for a function to be considered a metric.

5. How is a metric function used in practical applications?

Metric functions have numerous practical applications, such as in distance-based algorithms for data analysis, optimization problems, and pattern recognition. They are also used in physics, engineering, and other fields to measure distances between objects or points in a space.

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