Convergence of Quadratic Forms in $p$-Stable Random Variables and $\theta_p$-Radonifying Operators

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

In this paper, we obtain the upper exponential bounds for the tail probabilities of the quadratic forms for negatively dependent subgaussian random variables. In particular the law of iterated logarithm for quadratic forms of independent subgaussian random variables is generalized to the case of negatively dependent subgaussian random variables.

A Survey on Simulating Stable Random Variables

In general case, Chambers et al. (1976) introduced the following algorithm for simulating any stable random variables $ X/sim(alpha, beta, gamma, delta) $ with four parameters. They use a nonlinear transformation of two independent uniform random variables for simulating an stable random variable... (to continue, click here)

I the Distributions of Quadratic Forms on Normal Random Variables

Quadratic Forms in Unitary Operators

Dominated Convergence for Fuzzy Random Variables