Monotonicity of the incomplete gamma function with applications

Monotonicity of Ratios Involving Incomplete Gamma Functions with Actuarial Applications

Ratios involving incomplete gamma functions and their monotonicity properties play important roles in financial risk analysis. We derive desired monotonicity properties either using Pinelis’ Calculus Rules or applying probabilistic techniques. As a consequence, we obtain several inequalities involving conditional expectations that have been of interest in actuarial science.

Some monotonicity and limit results for the regularised incomplete gamma function

Letting P (u, x) denote the regularised incomplete gamma function, it is shown that for each α ≥ 0, P (x, x+ α) decreases as x increases on the positive real semiaxis, and P (x, x + α) converges to 1/2 as x tends to infinity. The statistical significance of these results is explored.

Monotonicity and Convexity for the Gamma Function

Let a and b be given real numbers with 0 ≤ a < b < a + 1. Then the function θa,b(x) = [Γ(x + b)/Γ(x + a)]1/(b−a) − x is strictly convex and decreasing on (−a,∞) with θa,b(∞) = a+b−1 2 and θa,b(−a) = a, where Γ denotes the Euler’s gamma function.

Monotonicity and inequalities for the gamma function

Monotonicity Results for the Gamma Function

The function [Γ(x+1)] 1/x x+1 is strictly decreasing on [1,∞), the function [Γ(x+1)]1/x √ x is strictly increasing on [2,∞), and the function [Γ(x+1)] 1/x √ x+1 is strictly increasing on [1,∞), respectively. From these, some inequalities, for example, the Minc-Sathre inequality, are deduced, and two open problems posed by the second author are solved partially.