General theorem for Functional dependence

In summary, if rank(DF) = k, it suggests functional dependence amongst the Fi's, and when rank(DF) < n, it signifies functional dependence amongst the variables in the function.
  • #1
chy1013m1
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0
suppose Fi (a1, a2, ... an) , 0 < i <= k. a1, ..., an are reals
Then the Frechet derivative DF is a k x n matrix. If rank(DF) = k , does it still suggest functional dependence amonst Fi 's ?
Also, when rank(DF) < n (number of independent variables) , what does it signify ?

The theorem I had in mind was :
let f = (f1, ..., fn) be a C1 map from a connected open set U in Rm into Rn.
Suppose Df has rank k at every x in U, where k < n.
Then every x in U has a neighborhood N s.t. f1, ..., fn are func.dep on N,
and f(N) is a smooth k-dim submanifold of Rn.
 
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  • #2
Yes, it still suggests functional dependence amongst the Fi's. When rank(DF) < n, it implies that some of the variables in the function are functionally dependent on the others, meaning that for any given set of values for some of the variables, there is a unique set of values for the remaining variables. This can be seen as a result of the theorem I mentioned above - it states that when the rank of the derivative is less than the number of independent variables, the function is functionally dependent.
 

1. What is a general theorem for functional dependence?

A general theorem for functional dependence is a mathematical statement that describes the relationship between two or more variables. It states that if one variable is functionally dependent on another, then the value of the dependent variable can be determined from the value of the independent variable.

2. What is the significance of functional dependence in science?

Functional dependence is important in science because it allows us to understand and predict how changes in one variable will affect another. This is essential for making accurate predictions and conducting experiments in various fields of science, such as physics, chemistry, and biology.

3. How can functional dependence be represented mathematically?

Functional dependence can be represented using equations or graphs. In an equation, the dependent variable is typically written as a function of the independent variable, such as y = f(x). In a graph, the dependent variable is plotted on the y-axis and the independent variable is plotted on the x-axis.

4. What is the difference between functional dependence and causality?

Functional dependence refers to the mathematical relationship between two variables, while causality refers to the cause-and-effect relationship between two events or phenomena. Functional dependence does not necessarily imply causality, as there could be other factors influencing the relationship between the variables.

5. How is functional dependence related to linear regression?

Functional dependence is the foundation of linear regression, which is a statistical method used to determine the relationship between two variables. In linear regression, the dependent variable is modeled as a linear function of the independent variable, allowing for the measurement of the strength and direction of the relationship between the two variables.

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