3.9 Uniform and Related Distributions
The distributions we consider in this section, along with a shorthand notation for each, are the:
- uniform distribution: U(a,b),
- multivariate uniform distribution: Un(Ω).
3.9.1 Uniform distribution
A uniform distribution has constant probability density on an interval (a, b) and zero probability density elsewhere. The distribution is specified by two parameters: the end points a and b. We denote the distribution U(a,b). Its PDF is
which is illustrated in Exhibit 3.13.
A U(a,b) random variable has CDF and inverse CDF:
The expectation, standard deviation, skewness, and kurtosis of a U(a,b) random variable are:
3.9.2 Multivariate uniform distribution
Let Ω ∈ n be a bounded region with volume (area) v(Ω). The multivariate uniform distribution on Ω is denoted Un(Ω) and has PDF
In applications, the distribution Un((0,1)n) often arises. If X ~ Un((0,1)n), its components Xi are independent random variables, each with marginal distribution U(0,1).
If U ~ U(0,1), how is V = 1 – U distributed?
If U ~ U(0,1), how is W = bU + a distributed for any constants a, b?
Suppose U ~ Un((0,1)n). What is Pr(Ui > 0.5 for all i)?
Suppose V ~ Un(Ω) where the region Ω is indicated in Exhibit 3.14.
- Is component V1 marginally uniformly distributed?
- Is component V2 marginally uniformly distributed?
- Are components V1 and V2 independent?