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In recent years, some interior-point methods have been suggested for convex minimization problems, but subgradient projection methods and related bundle methods of descent remain competitive. For convex minimization problems with very large number of dimensions, subgradient-projection methods are suitable, because they require little storage.
The following are among the properties of log-concave distributions: If a density is log-concave, so is its cumulative distribution function (CDF). If a multivariate density is log-concave, so is the marginal density over any subset of variables. The sum of two independent log-concave random variables is log-concave. This follows from the fact ...
The sum of two concave functions is itself concave and so is the pointwise minimum of two concave functions, i.e. the set of concave functions on a given domain form a semifield. Near a strict local maximum in the interior of the domain of a function, the function must be concave; as a partial converse, if the derivative of a strictly concave ...
As of 2018, all of them emphasize that medications are not required. However, medications, though imperfect, continue to be a component of treatment strategy for fibromyalgia patients. The German guidelines outlined parameters for drug therapy termination and recommended considering drug holidays after six months. [19]
The second derivative of a function f can be used to determine the concavity of the graph of f. [2] A function whose second derivative is positive is said to be concave up (also referred to as convex), meaning that the tangent line near the point where it touches the function will lie below the graph of the function.
If the signs differ, then the sequence is concave. In this example, the polygon is negatively oriented, but the determinant for the points F-G-H is positive, and so the sequence F-G-H is concave. The following table illustrates rules for determining whether a sequence of points is convex, concave, or flat:
Bone scans are conducted to rule out possible fractures and infections, magnetic resonance imaging (MRI) is used to eliminate the possibility of the spinal cord or nerve abnormalities, and computed tomography scans (CT scans) are used to get a more detailed image of the bones, muscles, and organs of the lumbar region.
Thus, the collection of −∞-convex measures is the largest such class, whereas the 0-convex measures (the logarithmically concave measures) are the smallest class. The convexity of a measure μ on n-dimensional Euclidean space R n in the sense above is closely related to the convexity of its probability density function. [2]