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The first alpha version of Bootstrap 4 was released on August 19, 2015. [16] The first beta version was released on August 10, 2017. [17] Otto suspended work on Bootstrap 3 on September 6, 2016, to free up time to work on Bootstrap 4. Bootstrap 4 was finalized on January 18, 2018. [18] Significant changes include: Major rewrite of the code
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 ...
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).
Boot is short for bootstrap [1] [2] or bootstrap load and derives from the phrase to pull oneself up by one's bootstraps. [3] [4] The usage calls attention to the requirement that, if most software is loaded onto a computer by other software already running on the computer, some mechanism must exist to load the initial software onto the ...
TinyMCE is an online rich-text editor released as open-source software under the GNU General Public License version 2 or later. [1] It converts HTML textarea fields, or other designated HTML elements, into editor instances. TinyMCE is designed to integrate with JavaScript libraries such as React, Vue.js, AngularJS and Bootstrap as well as ...
A permutation test (also called re-randomization test or shuffle test) is an exact statistical hypothesis test making use of the proof by contradiction. A permutation test involves two or more samples. The null hypothesis is that all samples come from the same distribution . Under the null hypothesis, the distribution of the test statistic is ...
v. t. e. In statistics and numerical analysis, isotonic regression or monotonic regression is the technique of fitting a free-form line to a sequence of observations such that the fitted line is non-decreasing (or non-increasing) everywhere, and lies as close to the observations as possible.
The state-space model can be nonlinear and the initial state and noise distributions can take any form required. Particle filter techniques provide a well-established methodology [2] [4] [5] for generating samples from the required distribution without requiring assumptions about the state-space model or the state distributions. However, these ...