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Bootstrapping (statistics) Bootstrapping is a procedure for estimating the distribution of an estimator by resampling (often with replacement) one's data or a model estimated from the data. [1] Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates. [2][3] This technique ...
List of free analog and digital electronic circuit simulators, available for Windows, macOS, Linux, and comparing against UC Berkeley SPICE. The following table is split into two groups based on whether it has a graphical visual interface or not. The latter requires a separate program to provide that feature, such as Qucs-S, [1] Oregano, [2] or ...
In computer technology, the term bootstrapping refers to language compilers that are able to be coded in the same language. (For example, a C compiler is now written in the C language. Once the basic compiler is written, improvements can be iteratively made, thus pulling the language up by its bootstraps).
Jackknife resampling. In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful for bias and variance estimation. The jackknife pre-dates other common resampling methods such as the bootstrap. Given a sample of size , a jackknife estimator can be built ...
Aldec. VHDL-1987,-1993,-2002,-2008,-2019 V1995, V2001, V2005, SV2009, SV2012, SV2017. Active-HDL is Aldec's Windows-based simulator with complete HDL graphical entry and verification environment aimed at FPGA and SoC FPGA applications. Riviera-PRO is Aldec's Windows/Linux-based simulator with complete verification environment aimed at FPGA, SoC ...
Bootstrapping (electronics) Bootstrapping is a technique in the field of electronics where part of the output of a system is used at startup. A bootstrap circuit is one where part of the output of an amplifier stage is applied to the input, so as to alter the input impedance of the amplifier. When applied deliberately, the intention is usually ...
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