In mathematics, a function f(x) between two ordered sets is unimodal if for some value m (the mode), it is monotonically increasing for x ? m and monotonically decreasing for x ? m. In that case, the maximum value of f(x) is f(m) and there are no other local maxima.

Examples of unimodal function:

• Quadratic polynomial
• Logistic map
• Tent map

Function \ f(x) is "S-unimodal" if its Schwartzian derivative is negative for all \ x \ne 0.

In probability and statistics, a "unimodal probability distribution" is a probability distribution whose probability density function is a unimodal function, or more generally, whose cumulative distribution function is convex up to m and concave thereafter (this allows for the possibility of a non-zero probability for x=m). For a unimodal probability distribution of a continuous random variable, the Vysochanskii-Petunin inequality provides a refinement of the Chebyshev inequality. Compare multimodal distribution.