parameters
101Implicit solvation — (sometimes known as continuum solvation) is a method of representing solvent as a continuous medium instead of individual “explicit” solvent molecules most often used in molecular dynamics simulations and in other applications of molecular… …
102Starmad — Infobox Software | name = STARMAD developer = [http://www.star n1.net Star n1 engineering] latest release version = 1.0.0 latest release date = January 1, 2008 operating system = Windows genre = Technical computing license = Proprietary website …
103combinatorics — /keuhm buy neuh tawr iks, tor , kom beuh /, n. (used with singular v.) See combinatorial analysis. * * * Branch of mathematics concerned with the selection, arrangement, and combination of objects chosen from a finite set. The number of possible… …
104Template:Cite web — [edit] [purge] …
105Metamaterial antenna — This Z antenna tested at the National Institute of Standards and Technology is smaller than a standard antenna with comparable properties. Its high efficiency is derived from the Z element inside the square that acts as a metamaterial, greatly… …
106Nuisance parameter — In statistics, a nuisance parameter is any parameter which is not of immediate interest but which must be accounted for in the analysis of those parameters which are of interest. The classic example of a nuisance parameter is the variance, σ2, of …
107Subroutine — In computer science, a subroutine (function, method, procedure, or subprogram) is a portion of code within a larger program, which performs a specific task and can be relatively independent of the remaining code. The syntax of many programming… …
108Electrical discharge machining — An electrical discharge machine Electric discharge machining (EDM), sometimes colloquially also referred to as spark machining, spark eroding, burning, die sinking or wire erosion,[1] is a manufacturing process whereby a desired shape is obtained …
109Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… …
110Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… …
