Logistic function: Difference between revisions

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| [[derivative]] || the derivative is <math>\frac{-e^{-x}}{(1 + e^{-x})^2}</math>.<br>If we denote the logistic function by the letter <math>g</math>, then we can also write the derivative as <math>g'(x) = g(x)g(-x) = g(x)(1 - g(x))</math>
| [[derivative]] || the derivative is <math>\frac{-e^{-x}}{(1 + e^{-x})^2}</math>.<br>If we denote the logistic function by the letter <math>g</math>, then we can also write the derivative as <math>g'(x) = g(x)g(-x) = g(x)(1 - g(x))</math>
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| [[second derivative]] || If we denote the logistic function by the letter <math>g</math>, then we can also write the derivative as <math>g''(x) = g'(x)(1 - 2g(x)) = g(x)(1 - g(x))(1 - 2g(x)) = g(x)g(-x)(1 - 2g(x)) = g(x)g(-x)(g(x) - g(-x))</math>
| [[second derivative]] || If we denote the logistic function by the letter <math>g</math>, then we can also write the derivative as <math>g''(x) = g'(x)(1 - 2g(x)) = g(x)(1 - g(x))(1 - 2g(x)) = g(x)g(-x)(1 - 2g(x)) = g(x)g(-x)(g(x) - g(-x))</math>
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| [[logarithmic derivative]] || the logarithmic derivative is <math>\frac{e^{-x}}{1 + e^{-x}}</math><br>If we denote the logistic function by <math>g</math>, the logarithmic derivative is <math>g(-x)</math>
| [[logarithmic derivative]] || the logarithmic derivative is <math>\frac{e^{-x}}{1 + e^{-x}}</math><br>If we denote the logistic function by <math>g</math>, the logarithmic derivative is <math>g(-x)</math>

Revision as of 21:11, 14 September 2014

Definition

The logistic function is a function with domain and range the open interval , defined as:

Equivalently, it can be written as:

Yet another form that is sometimes used, because it makes some aspects of the symmetry more evident, is:

For this page, we will denote the function by the letter .

We may extend the logistic function to a function , where and .

Probabilistic interpretation

The logistic function transforms the logarithm of the odds to the actual probability. Explicitly, given a probability (strictly between 0 and 1)of an event occurring, the odds in favor of are given as:

This could take any value in

The logarithm of odds is the expression:

If equals the above expression, then the function describing in terms of is the logistic function.

Key data

Item Value
default domain all of , i.e., all reals
range the open interval , i.e., the set
derivative the derivative is .
If we denote the logistic function by the letter , then we can also write the derivative as
second derivative If we denote the logistic function by the letter , then we can also write the derivative as
logarithmic derivative the logarithmic derivative is
If we denote the logistic function by , the logarithmic derivative is
antiderivative the function
critical points none
critical points for the derivative (correspond to points of inflection for the function) ; the corresponding point on the graph of the function is .
local maximal values and points of attainment none
local minimum values and points of attainment none
intervals of interest increasing and concave up on
increasing and concave down on
horizontal asymptotes asymptote at corresponding to the limit for
asymptote at corresponding to the limit for
inverse function inverse logistic function or log-odds function given by

Differentiation

First derivative

Consider the expression for :

We can differentiate this using the chain rule for differentiation (the inner function being and the outer function being the reciprocal function . We get:

Simplifying, we get:

We can write this in an alternate way that is sometimes more useful. We split the expression as a product:

The first factor on the right is , and the second factor is , so this simplifies to:

Functional equations

Symmetry equation

The logistic function has the property that its graph has symmetry about the point . Explicitly, it satisfies the functional equation:

We can see this algebraically:

Multiply numerator and denominator by , and get:

Differential equation

As discussed in the #First derivative section, the logistic function satisfies the condition:

Therefore, is a solution to the autonomous differential equation:

The general solution to that equation is the function where . The initial condition at pinpoints the logistic function uniquely.

Points and intervals of interest

Critical points

The function has no critical points. To see this, note that the derivative is:

Note that the numerator is never zero, nor is the denominator. Therefore, the function is always defined and nonzero.

Intervals of increase and decrease

The derivative:

is always positive. So the function is increasing on all of .

The asymptotic values are:

and:

In other words, the range of the function is the open interval , and it increases throughout its domain.

Points of inflection

The second derivative is:

We already noted that is always defined and nonzero, so the only way for to be zero is if < or . This solves to:

This solves to , or .

Thus, the second derivative is 0 at the point , i.e., with and .

Intervals of concave up and down

As above, we have:

We also noted that for all . Therefore, for and for . Therefore, is:

  • concave up for , i.e.,
  • concave down for , i.e.,

Symmetry

We discussed above a functional equation satisfied by :

From this, the following can be deduced:

  • The graph of has half-turn symmetry about the point .
  • is an even function. Note that this can also be seen from the actual expression: . But we don't need the actual expression to deduce that it is even -- the functional equation above gives evenness.
  • is an odd function. This can be directly deduced from being even, but can also be verified from the actual expression: .

Integration

First antiderivative

Direct computation

We have:

Computation in terms of functional equations for the logistic function

We have:

We also have that , so we get:

This can be rewritten as:

By the chain rule for differentiation, we get:

Thus:

This can be simplified and verified to be the same as the answer obtained by direct computation.