必应词典为您提供Tail-Probability-Function的释义,网络释义: 尾部概率函数;尾机率函数;
The chi-square approximation for likelihood drop is widely used but may be inaccurate for small to medium sized samples; mean and variance corrections may help. The Lugannani and Rice tail probability formula provides high accuracy based on a cumulant generating function, which is readily available...
Hence, the Chernoff bound on the tail probability for a standard normal random variable is Q(xo)≤exp(-xo22). The result of this example provides a convenient upper bound on the Q-function. Evaluating the Chernoff bound requires knowledge of the moment-generating function of the random variabl...
tail probabilitytransform functionqueueing theorydiscrete-time queueing systemObtaining (tail) probabilities from a transform function is an important topic in queueing theory. To obtain these probabilities in discrete-time queueing systems, we have to invert probability generating functions, since most ...
Then, I have other issues with the computation of the tail probability with thepnorm()function. On wikipedia, I can read that "The confidence interval can be expressed in terms of statistical significance, e.g.: "The 95% confidence interval represents values that are not statistically significa...
基本的idea应该是算tail probability，如果X服从标准正态分布，t>0. 那么:P(X>t)=1−Φ(t)≈...
Physics - Plasma PhysicsMathematical PhysicsAn analytical derivation of the probability density function (PDF) tail describing the strongly correlated interface growth governed by the nonlinear Kardar-Parisi-Zhang equation is provided. The PDF tail exactly coincides with a Tracy-Widom distribution i.e. ...
或者是翻译成了其他名字，所以请问这里的tail bo…基本的idea应该是算tail probability，如果X服从标准正...
Fig. 1 Observed rainfall and discharge (in mm/d) as a function of the return period. Extrapolation by the ER bivariate model. Display full size Fig. 2 Synthetic rainfall and runoff distributions with very low retention capacity. Rainfall ev index = 0.5; B = 50 mm. Display full ...
Then, with probability 1, the sample variance satisfies σ2 ≤γ2 σ2 with γ2 given by 1.6 . Proof. Using the representation 1.3 of the sample variance as an U-statistic, it suffices to show that the function f : Rn → R, f x xi − xk 2, x x1, . . . , xn ∈ Rn, i...