Empirical Distribution Function - Definition

Definition

Let (x1, …, xn) be iid real random variables with the common cdf F(t). Then the empirical distribution function is defined as

 \hat F_n(t) = \frac{ \mbox{number of elements in the sample} \leq t}n =
\frac{1}{n} \sum_{i=1}^n \mathbf{1}\{x_i \le t\},

where 1{A} is the indicator of event A. For a fixed t, the indicator 1{xit} is a Bernoulli random variable with parameter p = F(t), hence is a binomial random variable with mean nF(t) and variance nF(t)(1 − F(t)). This implies that is an unbiased estimator for F(t).

Read more about this topic:  Empirical Distribution Function

Famous quotes containing the word definition:

    I’m beginning to think that the proper definition of “Man” is “an animal that writes letters.”
    Lewis Carroll [Charles Lutwidge Dodgson] (1832–1898)

    The physicians say, they are not materialists; but they are:MSpirit is matter reduced to an extreme thinness: O so thin!—But the definition of spiritual should be, that which is its own evidence. What notions do they attach to love! what to religion! One would not willingly pronounce these words in their hearing, and give them the occasion to profane them.
    Ralph Waldo Emerson (1803–1882)

    Beauty, like all other qualities presented to human experience, is relative; and the definition of it becomes unmeaning and useless in proportion to its abstractness. To define beauty not in the most abstract, but in the most concrete terms possible, not to find a universal formula for it, but the formula which expresses most adequately this or that special manifestation of it, is the aim of the true student of aesthetics.
    Walter Pater (1839–1894)