Darmois–Skitovich theorem

The Darmois–Skitovich theorem  is one of the most famous characterization theorems of mathematical statistics. It characterizes the normal distribution (the Gaussian distribution) by the independence of two linear forms from independent random variables. This theorem was proved independently by G. Darmois and V. P. Skitovich in 1953.

Formulation[]

Let ${\displaystyle \xi _{j},j=1,2,\ldots ,n,n\geq 2}$  be independent random variables. Let ${\displaystyle \alpha _{j},\beta _{j}}$  be nonzero constants. If the linear forms ${\displaystyle L_{1}=\alpha _{1}\xi _{1}+\cdots +\alpha _{n}\xi _{n}}$ and ${\displaystyle L_{2}=\beta _{1}\xi _{1}+\cdots +\beta _{n}\xi _{n}}$ are independent then all random variables ${\displaystyle \xi _{j}}$ have normal distributions (Gaussian distributions).

History[]

The Darmois–Skitovich theorem is a generalization of the Kac–Bernstein theorem in which the normal distribution (the Gaussian distribution) is characterized by the independence of the sum and the difference of two independent random variables. For a history of proving the theorem by V. P. Skitovich, see the article ^[1]

Information sources[]

• Darmois, G. (1953). Analyse generale des liaisons stochastiques. Rev.Inst.Intern.Stat (21): 2—8.
• Skitivic, V. P. (1953). "On a property of the normal distribution." Dokl. Akad. Nauk SSSR (N.S.) (89): 217—219 (in Russian).
• A. M. Kagan, Yu. V. Linnik, and C. R. Rao, Characterization Problems in Mathematical Statistics, Wiley, New York (1973).

References[]