gives the logistic sigmoid function.
LogisticSigmoid
gives the logistic sigmoid function.
Details
- Mathematical function, suitable for both symbolic and numeric manipulation.
- LogisticSigmoid is also known as logistic function or sigmoid function, and the inverse is known as logit or log-odds.
- The logistic function
is a solution to the differential equation
. - LogisticSigmoid[z] has no branch cut discontinuities.
- LogisticSigmoid can be evaluated to arbitrary numerical precision.
- LogisticSigmoid automatically threads over lists. »
- LogisticSigmoid can be used with Interval and CenteredInterval objects. »
- In TraditionalForm, the logistic sigmoid function is sometimes denoted as
.
Examples
open all close allBasic Examples (5)
LogisticSigmoid[2.]Plot over a subset of the reals:
Plot[LogisticSigmoid[x], {x, -4, 4}]Plot over a subset of the complexes:
ComplexPlot3D[LogisticSigmoid[z], {z, -2 - 2I, 2 + 2I}, PlotLegends -> Automatic]Series expansion at the origin:
Series[LogisticSigmoid[x], {x, 0, 10}]The expansion of the function:
LogisticSigmoid[x]//FunctionExpandScope (36)
Numerical Evaluation (6)
LogisticSigmoid[.8]N[LogisticSigmoid[1 / 9], 50]The precision of the output tracks the precision of the input:
LogisticSigmoid[1.0000000000000000000000]N[LogisticSigmoid[1 + 9 I]]Evaluate efficiently at high precision:
LogisticSigmoid[2 / 7`100]//TimingLogisticSigmoid[5 / 11`100000];//TimingCompute worst-case guaranteed intervals using Interval and CenteredInterval objects:
LogisticSigmoid[Interval[{0.5, 0.6}]]LogisticSigmoid[CenteredInterval[1 / 2, 1 / 100]]Or compute average-case statistical intervals using Around:
LogisticSigmoid[ Around[2, 0.01]]Compute the elementwise values of an array using automatic threading:
LogisticSigmoid[{{2I π, 0}, {0, 2I π}}]Or compute the matrix LogisticSigmoid function using MatrixFunction:
MatrixFunction[LogisticSigmoid, {{2I π, 0}, {0, 2I π}}]//FullSimplifySpecific Values (4)
The value of LogisticSigmoid at 2 πI n for integer n is 1/2:
Table[LogisticSigmoid[2 I π n], {n, -1, 3}]LogisticSigmoid[Infinity]LogisticSigmoid[-Infinity]Simple exact values are generated automatically:
LogisticSigmoid[0]More complicated cases require explicit use of FunctionExpand:
LogisticSigmoid[I π / 2]FunctionExpand[%]Find a value of
for which the
using Solve:
Solve[LogisticSigmoid[x] == 0.8, x, Reals]//Quietxval = x /. First[%]Plot[LogisticSigmoid[x], {x, -5, 5}, Epilog -> Style[Point[{xval, LogisticSigmoid[xval]}], PointSize[Large], Red]]Visualization (3)
Plot the LogisticSigmoid[x] function:
Plot[LogisticSigmoid[x], {x, 0, 4}]ComplexContourPlot[Re[LogisticSigmoid[z]], {z, -4 - 4 I, 4 + 4 I}, Contours -> 20]ComplexContourPlot[Im[LogisticSigmoid[z]], {z, -4 - 4 I, 4 + 4 I}, Contours -> 20]PolarPlot[LogisticSigmoid[ϕ], {ϕ, -2π, 8π}, Frame -> True]Function Properties (10)
LogisticSigmoid is defined for all real and complex values:
FunctionDomain[LogisticSigmoid[x], x]FunctionDomain[LogisticSigmoid[z], z, Complexes]LogisticSigmoid achieves all values between 0 and 1 on the reals:
FunctionRange[LogisticSigmoid[x], x, y]FunctionRange[LogisticSigmoid[z], z, y, Complexes]LogisticSigmoid has the mirror property
:
FullSimplify[LogisticSigmoid[Conjugate[z]] == Conjugate[LogisticSigmoid[z]]]LogisticSigmoid is an analytic function of x:
FunctionAnalytic[LogisticSigmoid[x], x]It has no singularities or discontinuities:
FunctionSingularities[LogisticSigmoid[x], x]FunctionDiscontinuities[LogisticSigmoid[x], x]LogisticSigmoid is nondecreasing:
FunctionMonotonicity[LogisticSigmoid[x], x]LogisticSigmoid is injective:
FunctionInjective[LogisticSigmoid[x], x]Plot[{LogisticSigmoid[x], .8}, {x, -5, 5}]LogisticSigmoid is not surjective:
FunctionSurjective[LogisticSigmoid[x], x]Plot[{LogisticSigmoid[x], -1}, {x, -5, 5}]LogisticSigmoid is non-negative:
FunctionSign[LogisticSigmoid[x], x]LogisticSigmoid is neither convex nor concave:
FunctionConvexity[LogisticSigmoid[x], x]TraditionalForm formatting:
LogisticSigmoid[z]//TraditionalFormDifferentiation (3)
First derivative with respect to z:
D[LogisticSigmoid[z], z]Higher derivatives with respect to z:
Table[D[LogisticSigmoid[z], {z, k}], {k, 1, 3}]//FullSimplifyPlot the higher derivatives with respect to z:
Plot[%, {z, -5, 5}, PlotLegends -> {"First Derivative", "Second Derivative", "Third Derivative"}]Formula for the ![]()
derivative with respect to z:
D[LogisticSigmoid[z], {z, k}]// FullSimplifyIntegration (3)
Compute the indefinite integral using Integrate:
Integrate[LogisticSigmoid[x], x]FullSimplify[D[%, x]]Integrate[LogisticSigmoid[x], {x, 0, 5}]Integrate[Exp[-x] LogisticSigmoid[x], x]//FullSimplifyIntegrate[ x LogisticSigmoid[x^2], {x, 0, 3}]//FullSimplifySeries Expansions (3)
Find the Taylor expansion using Series:
Series[LogisticSigmoid[x], {x, 0, 7}]Plots of the first three approximations around
:
terms = Normal@Table[Series[LogisticSigmoid[x], {x, 0, m}], {m, 1, 5, 2}];
Plot[{LogisticSigmoid[x], terms}, {x, -10, 10}]Find the series expansion at Infinity:
Series[LogisticSigmoid[x], {x, Infinity, 1}]Taylor expansion at a generic point:
Series[LogisticSigmoid[x], {x, x0, 2}]//Normal// FullSimplifyFunction Representations (4)
LogisticSigmoid can be represented in terms of Exp:
FullSimplify[LogisticSigmoid[x] == (Exp[x]/Exp[x] + 1)]GeneratingFunction[((-1)^kEulerE[k, 0]/2k!), k, x] == LogisticSigmoid[x]//FullSimplifyLogisticSigmoid can be represented in terms of MeijerG:
(1 + (MeijerG[{{}, {}}, {{0, (1/2)}, {}}, (x/2), (1/2)]/Sqrt[π]))^-1 == LogisticSigmoid[x]//FullSimplifyLogisticSigmoid obeys the logistic differential equation
:
y'[x] == y[x](1 - y[x]) /. y -> LogisticSigmoidApplications (1)
Write a specific solution to the dimensionless logistic equation using LogisticSigmoid:
y'[x] - y[x] * (1 - y[x]) == 0 /. y -> Function[{x}, LogisticSigmoid[x]] // SimplifySee Also
Exp LogisticDistribution UnitStep HeavisideTheta
Function Repository: Logit SmoothStep RationalSmoothStep
Related Guides
Related Links
History
Text
Wolfram Research (2014), LogisticSigmoid, Wolfram Language function, https://reference.wolfram.com/language/ref/LogisticSigmoid.html.
CMS
Wolfram Language. 2014. "LogisticSigmoid." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/LogisticSigmoid.html.
APA
Wolfram Language. (2014). LogisticSigmoid. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/LogisticSigmoid.html
BibTeX
@misc{reference.wolfram_2026_logisticsigmoid, author="Wolfram Research", title="{LogisticSigmoid}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/LogisticSigmoid.html}", note=[Accessed: 13-June-2026]}
BibLaTeX
@online{reference.wolfram_2026_logisticsigmoid, organization={Wolfram Research}, title={LogisticSigmoid}, year={2014}, url={https://reference.wolfram.com/language/ref/LogisticSigmoid.html}, note=[Accessed: 13-June-2026]}