Exact distributions and asymptotic expansions derived for sums and differences of independent non-central gamma random variables, including closed-form coefficients for the product of correlated normals.
Right-tail asymptotics for products of independent normal random variables
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abstract
Let $X_1,\dots,X_n$ be independent normal random variables with $X_i\sim N(\mu_i,\sigma_i^2)$, and set $Z=\prod_{i=1}^n X_i$. We derive asymptotic approximations for the right tail probability $\mathbb{P}(Z>x)$ as $x\to\infty$. When at least one mean is nonzero, the asymptotic formula remains explicit and involves a finite multiplicative factor arising from admissible sign patterns (reflecting the different ways the product can be positive); it includes an explicit first relative correction term of order $x^{-1/n}$, with remaining relative error $O(x^{-2/n})$. The proof uses a boundary saddle-point/Laplace method: first a multidimensional Laplace approximation near the boundary saddle, then a one-dimensional endpoint Laplace approximation.
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math.PR 1years
2026 1verdicts
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The non-central gamma sum and difference distributions: exact distribution and asymptotic expansions
Exact distributions and asymptotic expansions derived for sums and differences of independent non-central gamma random variables, including closed-form coefficients for the product of correlated normals.