Logistic function: Difference between revisions
Line 41: | Line 41: | ||
| [[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> | ||
|- | |- | ||
| [[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) | | [[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> | ||
|- | |- | ||
| [[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.