Mathematical functions for BUGS and nimbleFunction programmingNIMBLE Development Team
Here I present a small library of mathematically oriented subfunctions, encompassing functions for Matrix & Vector manipulation, Trigonometric functions, Complex Number functions, Factorial functions & Geometric functions.Information about the purpose each function and its required arguments is detailed in ...
inverse function- a function obtained by expressing the dependent variable of one function as the independent variable of another; f and g are inverse functions if f(x)=y and g(y)=x Kronecker delta- a function of two variables i and j that equals 1 when i=j and equals 0 otherwise ...
Mathematical Programming, the official journal of the Mathematical Optimization Society, is dedicated to publishing original articles that address every facet of mathematical optimization. This includes all considerations related to the optimization of a functions of multiple variables, often subject to a se...
4.3.2.2.2 Linear programming The linear programming (LP) in continuous variables, with values in R+ or a subset of R+, consists in optimizing a criterion, otherwise called objective function, calculated from some of the variables using a formula, while assuring that constraints on the variables...
Mathematical Programming, the official journal of the Mathematical Optimization Society, is dedicated to publishing original articles that address every facet of mathematical optimization. This includes all considerations related to the optimization of a functions of multiple variables, often subject to a se...
r-Invex functionDualityAn η-approximation approach introduced by Antczak [T. Antczak, A new method of solving nonlinear mathematical programming problems involving r-invex functions, J. Math. Anal. Appl. 311 (2005) 313–323] is used to obtain a solution Mond–Weir dual problems involving r-...
Schrijver, Cones of matrices and set-functions and 0–1 optimization,SIAM Journal on Optimization 1 (2) (1991) 166–190. Article MATH MathSciNet Google Scholar Y.E. Nesterov and A.S. Nemirovskii,Interior Point Polynomial Algorithms in Convex Programming (SIAM, Philadelphia, PA, 1994). ...
Ghadimi, S., Lan, G.: Accelerated gradient methods for nonconvex nonlinear and stochastic programming. Math. Program. 156, 59–99 (2016) Article MathSciNet Google Scholar Grohs, P., Hosseini, S.: ϵ-subgradient algorithms for locally lipschitz functions on Riemannian manifolds. Adv. Comput...
Optimality conditions for non-finite valued convex composite functions. James V. BurkeR. A. Poliquin 原文链接 谷歌学术 必应学术 百度学术 Generalizations of Slater's constraint qualification for infinite convex programs. Vaithilingam JeyakumarHenry Wolkowicz ...