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Rendezvous or highest random weight (HRW) hashing [1] [2] is an algorithm that allows clients to achieve distributed agreement on a set of options out of a possible set of options. A typical application is when clients need to agree on which sites (or proxies) objects are assigned to.
The Go programming language has built-in types complex64 (each component is 32-bit float) and complex128 (each component is 64-bit float). Imaginary number literals can be specified by appending an "i". The Perl core module Math::Complex provides support for complex numbers. Python provides the built-in complex type. Imaginary number literals ...
There are many variations of the weighted majority algorithm to handle different situations, like shifting targets, infinite pools, or randomized predictions. The core mechanism remains similar, with the final performances of the compound algorithm bounded by a function of the performance of the specialist (best performing algorithm) in the pool.
Given the same setup with N experts. Consider the special situation where the proportions of experts predicting positive and negative, counting the weights, are both close to 50%. Then, there might be a tie. Following the weight update rule in weighted majority algorithm, the predictions made by the algorithm would be randomized.
The difference between the full capitalization, float-adjusted, and equal weight versions is in how the index components are weighted. The full cap index uses the total shares outstanding for each company. The float-adjusted index uses shares adjusted for free float. The equal-weighted index assigns each security in the index the same weight.
Map of all countries in the S&P 1200 as of Jan 21, 2019. The S&P Global 1200 Index is a free-float weighted stock market index of global equities from Standard & Poor's.The index was launched on Sep 30, 1999 and covers 31 countries and approximately 70 percent of global stock market capitalization. [1]
from collections.abc import Sequence def simpson_nonuniform (x: Sequence [float], f: Sequence [float])-> float: """ Simpson rule for irregularly spaced data.:param x: Sampling points for the function values:param f: Function values at the sampling points:return: approximation for the integral See ``scipy.integrate.simpson`` and the underlying ...
For example, the S&P 500 index is both cap-weighted and float-adjusted. [3] Historically, in the United States, capitalization-weighted indices tended to use full weighting, i.e., all outstanding shares were included, while float-weighted indexing has been the norm in other countries, perhaps because of large cross-holdings or government ownership.