bootstrap


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bootstrap

[′büt‚strap]
(computer science)
The procedures for making a computer or a program function through its own actions.
(engineering)
A technique or device designed to bring itself into a desired state by means of its own action.

bootstrap

(operating system, compiler)
To load and initialise the operating system on a computer. Normally abbreviated to "boot". From the curious expression "to pull oneself up by one's bootstraps", one of the legendary feats of Baron von Munchhausen. The bootstrap loader is the program that runs on the computer before any (normal) program can run. Derived terms include reboot, cold boot, warm boot, soft boot and hard boot.

The term also applies to the use of a compiler to compile itself. The usual process is to write an interpreter for a language, L, in some other existing language. The compiler is then written in L and the interpreter is used to run it. This produces an executable for compiling programs in L from the source of the compiler in L. This technique is often used to verify the correctness of a compiler. It was first used in the LISP community.

See also My Favourite Toy Language.
References in periodicals archive ?
Nurturing innovation through bootstrap financing - An entrepreneurial perspective.
In order to adjust for heteroskedasticity, Deaton (1997, 71) suggested using bootstrap estimates to correct the standard errors that are essential for inference.
It is for this reason that bootstrap techniques are adopted by Simar and Wilson (2000, 2007).
The purpose of this paper is to explore the use of bootstrap statistics in estimating the variances and biases of selected robust estimates of the parameters of a linear model, specifically, the variance and bias of [beta] obtained from the following robust alternatives: 1) median approach (Padua, 1987); 2) the generalized bootstrap estimate of [beta]; and 3) and the minimum absolute deviation method (Huber, 2009) are estimated by the bootstrap methods.
Due to this situation, the obtainment of accurate estimates becomes more serious when the sample to be submitted to the application of the bootstrap method provides a significant amount of outliers.
Repeat steps 2-4 B times to obtain B sets of bootstrap parameter estimates for inference.
Based on the bootstrap sample, calculate the bootstrap CUSUM, denoted [S.
Eneste articulo se utilizael bootstrap no parametrico debido a su amplio uso en diferentes aplicaciones, lo cual es impulsado por su sencillez en la implementacion ademas de diferentes argumentos a su favor como lo que expresa Chernick (2008) quien afirma que una motivacion para su uso es que la distribucion empirica es el estimador de maxima verosimilitud de la distribucion de los datos (F) cuando no hay supuestos acerca de esta.
As the Revere America Foundation wrote in an amicus brief about EMTALA and the resulting free riders as a justification for the individual mandate, "that problem is of Congress' own creation, and Congress cannot bootstrap itself into powers not enumerated by the Constitution simply because it deems the exercise of those powers expedient in light of other regulations that it has previously enacted.
Another major update to Bootstrap 2 is the way it is delivered.
The BCa bootstrap adjusts for both bias and skewness in the bootstrap distribution (Efron and Tibshirani, 1993), and is available as an option in the software packages mentioned above.
They present a textbook for an elementary one-semester or one-quarter course in bootstrap methods, improving on Chernick's earlier text.