A family of independent random variables is independent and identically distributed when every variable has the same probability distribution.
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- Affine autoregressive process
- Aggregate claims model
- Bernoulli source
- Bühlmann model
- Canonical model of an independent and identically distributed sequence
- Conditional expectation of a summand given future partial sums
- Empirical characteristic function
- Exchangeable random variables
- Exponential martingale of a random walk
- Exponential moment bound for a Gaussian random-walk maximum
- Exponential moment of a renewal count
- Fair-coin doubling martingale
- Fixed-design nonparametric regression
- Gaussian rotation interpolation inequality
- Gaussian rotation of independent copies
- Geometric-sum moment-generating function
- Infinite occupation time of one-dimensional Brownian motion
- Integrability of a stopped random-walk increment
- Kernel density estimation
- Max-stable distribution
- Method of types
- M-G-1 queue
- Minimum size of a sufficient set for an IID source
- Normal mean and variance maximum-likelihood estimators
- One-nearest-neighbour classifier
- Order symmetry of independent random variables
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- Probability content of a nearest neighbour ball
- Rademacher complexity
- Rademacher symmetrization inequality
- Sample maximum
- Statistical sample
- Strong law for adjacent products
- Strong law of large numbers
- Strong white noise
- Weak law from a characteristic-function expansion
- Weak law of large numbers
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