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If a density is log-concave, so is its survival function. [3] If a density is log-concave, it has a monotone hazard rate (MHR), and is a regular distribution since the derivative of the logarithm of the survival function is the negative hazard rate, and by concavity is monotone i.e.
The Brunn–Minkowski inequality asserts that the Lebesgue measure is log-concave. The restriction of the Lebesgue measure to any convex set is also log-concave.. By a theorem of Borell, [2] a probability measure on R^d is log-concave if and only if it has a density with respect to the Lebesgue measure on some affine hyperplane, and this density is a logarithmically concave function.
The logarithm function () = is concave on its domain (,), as its derivative is a strictly decreasing function. Any affine function f ( x ) = a x + b {\displaystyle f(x)=ax+b} is both concave and convex, but neither strictly-concave nor strictly-convex.
The rows of Pascal's triangle are examples for logarithmically concave sequences. In mathematics, a sequence a = (a 0, a 1, ..., a n) of nonnegative real numbers is called a logarithmically concave sequence, or a log-concave sequence for short, if a i 2 ≥ a i−1 a i+1 holds for 0 < i < n.
In atmospheric science, log-normal distributions (or distributions made by combining multiple log-normal functions) have been used to characterize both measurements and models of the sizes and concentrations of many different types of particles, from volcanic ash, to clouds and rain, to airborne microbes.
WASHINGTON (Reuters) -U.S. President Donald Trump said on Sunday, without citing evidence, that "certain classes of people" in South Africa were being treated "very badly" and that he would cut ...
Image source: Getty Images. Social Security's earnings test limits also rose in 2025. This year, seniors who work and collect benefits will be able to earn more money without risking having a ...
The use of log probabilities improves numerical stability, when the probabilities are very small, because of the way in which computers approximate real numbers. [1] Simplicity. Many probability distributions have an exponential form. Taking the log of these distributions eliminates the exponential function, unwrapping the exponent.