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Stein's lemma, named in honor of Charles Stein, is a theorem of probability theory that is of interest primarily because of its applications to statistical inference — in particular, to James–Stein estimation and empirical Bayes methods — and its applications to portfolio choice theory. [1]
The Gaussian VaR ensures subadditivity: for example, the Gaussian VaR of a two unitary long positions portfolio at the confidence level is, assuming that the mean portfolio value variation is zero and the VaR is defined as a negative loss, = + + where is the inverse of the normal cumulative distribution function at probability level , , are the ...
In probability theory, Wald's equation, Wald's identity [1] or Wald's lemma [2] is an important identity that simplifies the calculation of the expected value of the sum of a random number of random quantities.
It should only contain pages that are Probability theorems or lists of Probability theorems, as well as subcategories containing those things (themselves set categories). Topics about Probability theorems in general should be placed in relevant topic categories .
Stein's method is a general method in probability theory to obtain bounds on the distance between two probability distributions with respect to a probability metric.It was introduced by Charles Stein, who first published it in 1972, [1] to obtain a bound between the distribution of a sum of -dependent sequence of random variables and a standard normal distribution in the Kolmogorov (uniform ...
Theorem (Achlioptas, 2003, Theorem 1.1) — Let the random projection matrix have entries drawn i.i.d., either from R i j = { + 1 with probability 1 / 2 − 1 with probability 1 / 2 {\displaystyle R_{ij}={\begin{cases}+1&{\text{ with probability }}1/2\\-1&{\text{ with probability }}1/2\end{cases}}}
The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. [1] These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases. [2] There are several other (equivalent) approaches to formalising ...
Neyman–Pearson lemma [5] — Existence:. If a hypothesis test satisfies condition, then it is a uniformly most powerful (UMP) test in the set of level tests.. Uniqueness: If there exists a hypothesis test that satisfies condition, with >, then every UMP test in the set of level tests satisfies condition with the same .