gives the inverse of the regularized incomplete gamma function.
InverseGammaRegularized
gives the inverse of the regularized incomplete gamma function.
Details
- Mathematical function, suitable for both symbolic and numerical manipulation.
- With the regularized incomplete gamma function defined by
, InverseGammaRegularized[a,s] is the solution for
in
. - InverseGammaRegularized[a,z0,s] gives the inverse of GammaRegularized[a,z0,z].
- Note that the arguments of InverseGammaRegularized are arranged differently than in InverseBetaRegularized.
- For certain special arguments, InverseGammaRegularized automatically evaluates to exact values.
- InverseGammaRegularized can be evaluated to arbitrary numerical precision.
- InverseGammaRegularized automatically threads over lists.
Examples
open all close allBasic Examples (3)
Scope (30)
Numerical Evaluation (5)
Evaluate numerically to high precision:
N[InverseGammaRegularized[2, 33 / 100], 50]The precision of the output tracks the precision of the input:
InverseGammaRegularized[2, 0.330000000000000000000000]Evaluate InverseGammaRegularized efficiently at high precision:
InverseGammaRegularized[2, 0.33`500]//TimingInverseGammaRegularized[2, 0.33`10000];//TimingEvaluate the three-argument generalized case:
InverseGammaRegularized[4, 3 / 4, 0.2]Compute average-case statistical intervals using Around:
InverseGammaRegularized[ Around[2 / 3, 0.001], 1 / 3]Compute the elementwise values of an array:
InverseGammaRegularized[1, {{1 / 2, 1 / 5}, {1 / 3, 1 / 2}}]Or compute the matrix InverseGammaRegularized function using MatrixFunction:
MatrixFunction[InverseGammaRegularized[1, #]&, {{1 / 2, 1 / 5}, {1 / 3, 1 / 2}}]//FullSimplifySpecific Values (3)
Table[InverseGammaRegularized[a, 0], {a, 1, 5}]Table[InverseGammaRegularized[a, 1], {a, 1, 5}]f[s_] := InverseGammaRegularized[2, s] - 1;
szero = Solve[f[s] == 0 && 0 < s < 1, s][[1, 1, 2]]Plot[f[s], {s, 0, 1}, Epilog -> Style[Point[{szero, f[szero]}], PointSize[Large], Red]]FunctionDomain[InverseGammaRegularized[a, s], s]Visualization (2)
Function Properties (8)
Real domain of InverseGammaRegularized:
FunctionDomain[InverseGammaRegularized[a, x], {a, x}]Its complex domain is the same:
FunctionDomain[InverseGammaRegularized[a, x], {a, x}, Complexes]//ReduceThe range of InverseGammaRegularized is the non-negative reals:
FunctionRange[InverseGammaRegularized[a, x], x, y]InverseGammaRegularized is not an analytic function:
FunctionAnalytic[InverseGammaRegularized[a, x], {a, x}]It has both singularities and discontinuities:
FunctionSingularities[InverseGammaRegularized[a, x], {a, x}]FunctionDiscontinuities[InverseGammaRegularized[a, x], {a, x}]For a fixed value of
,
is nonincreasing on its
domain:
FunctionMonotonicity[{InverseGammaRegularized[a, x], 0 < x <= 1}, x, Assumptions -> a > 0]For a fixed value of
,
is an injective function of
:
FunctionInjective[InverseGammaRegularized[a, x], x, Assumptions -> a > 0]Plot[{InverseGammaRegularized[2, x], 3}, {x, -1, 1}]InverseGammaRegularized is not surjective:
FunctionSurjective[InverseGammaRegularized[a, x], x, Assumptions -> a > 0]Plot[{InverseGammaRegularized[2, x], -2}, {x, -1, 1}]InverseGammaRegularized is non-negative on its domain:
FunctionSign[{InverseGammaRegularized[a, x], 0 < x <= 1 && a > 0}, {x, a}]InverseGammaRegularized is neither convex nor concave:
FunctionConvexity[{InverseGammaRegularized[a, x], 0 < x <= 1 && a > 0}, {x, a}]Differentiation (3)
First derivative of the inverse of the regularized incomplete gamma function:
D[InverseGammaRegularized[a, s], s]derivs = Table[D[InverseGammaRegularized[a, s], {s, n}], {n, 1, 3}]//SimplifyPlot[Evaluate[derivs /. a -> 1], {s, 0, 1}, PlotLegends -> {"First Derivative", "Second Derivative", "Third Derivative"}]First derivative of the inverse of the generalized regularized incomplete gamma function:
D[InverseGammaRegularized[a, z0, s], s]Integration (2)
Series Expansions (3)
Taylor expansion for InverseGammaRegularized around
:
Series[InverseGammaRegularized[a, s], {s, 0.5, 3}]//TraditionalFormPlot the first three approximations for
around
:
terms = Normal@Table[Series[InverseGammaRegularized[1, s], {s, 0.5, m}], {m, 1, 3}];
Plot[{InverseGammaRegularized[1, s], terms}, {s, 0, 2}]Series expansion of InverseGammaRegularized at a generic point:
Series[InverseGammaRegularized[a, s], {s, s0, 1}]Series expansion of the three-parameter InverseGammaRegularized function at a generic point:
Series[InverseGammaRegularized[a, z0, s], {z0, z, 1}]Series[InverseGammaRegularized[a, z0, s], {a, a0, 1}]//TraditionalFormFunction Identities and Simplifications (2)
Primary definition of InverseGammaRegularized:
Solve[GammaRegularized[a, z] == s, z]//QuietFunction relation to its inverse:
Table[GammaRegularized[3.5, InverseGammaRegularized[3.5, s]] == s, {s, 0, 1, 0.01}]//UnionTable[InverseGammaRegularized[1.5, GammaRegularized[1.5, x]] == x, {x, 0, 1, 0.01}]//UnionOther Features (2)
InverseGammaRegularized threads elementwise over lists and matrices:
InverseGammaRegularized[2 / 3, {0.2, 0.3, 0.4, 0.5}]InverseGammaRegularized[2 / 3, (| | |
| :- | :- |
| 0 | u |
| v | 1 |)]//MatrixFormTraditionalForm formatting:
InverseGammaRegularized[a, s] // TraditionalFormGeneralizations & Extensions (1)
InverseGammaRegularized threads element-wise over lists:
InverseGammaRegularized[2 / 3, {0.2, 0.3, 0.4, 0.5}]Applications (2)
Model the PDF of the gamma distribution through uniformly distributed random numbers:
pmod[α_, n_] := InverseGammaRegularized[α, ∞, RandomReal[{0, 1}, n] - 1]Compare binned modeled distribution with exact distribution:
With[{α = 2, n = 2000, s = 0.5},
Show[{ListPlot[{First[#], Length[#] / n / s}& /@ Split[Sort[Round[pmod[α, n], s]]]],
Plot[x ^ (α - 1) / (E ^ x Gamma[α]) , {x, 0, 8}]}]]Quartiles for a derived distribution:
Quartiles[TransformedDistribution[x^2, xNormalDistribution[]]]data = RandomVariate[NormalDistribution[], 10 ^ 3];Quartiles[HistogramDistribution[data]]Properties & Relations (2)
InverseGammaRegularized is the inverse of GammaRegularized:
InverseGammaRegularized[3.5, 0.66]GammaRegularized[3.5, %]Solve a transcendental equation:
Solve[InverseGammaRegularized[α, x] ^ 2 + 2InverseGammaRegularized[α, x] == 1, x]Possible Issues (2)
InverseGammaRegularized evaluates numerically only for
:
InverseGammaRegularized[2, 1.2]In TraditionalForm,
is not automatically InverseGammaRegularized:
Q^-1(a, z)Tech Notes
Related Guides
Related Links
History
Introduced in 1996 (3.0)
Text
Wolfram Research (1996), InverseGammaRegularized, Wolfram Language function, https://reference.wolfram.com/language/ref/InverseGammaRegularized.html.
CMS
Wolfram Language. 1996. "InverseGammaRegularized." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/InverseGammaRegularized.html.
APA
Wolfram Language. (1996). InverseGammaRegularized. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/InverseGammaRegularized.html
BibTeX
@misc{reference.wolfram_2026_inversegammaregularized, author="Wolfram Research", title="{InverseGammaRegularized}", year="1996", howpublished="\url{https://reference.wolfram.com/language/ref/InverseGammaRegularized.html}", note=[Accessed: 13-June-2026]}
BibLaTeX
@online{reference.wolfram_2026_inversegammaregularized, organization={Wolfram Research}, title={InverseGammaRegularized}, year={1996}, url={https://reference.wolfram.com/language/ref/InverseGammaRegularized.html}, note=[Accessed: 13-June-2026]}