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Algorithm: In mathematics and computer science, an algorithm ) is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing, automated reasoning, and other tasks.
Algorithmic trading: Algorithmic trading is a method of executing a large order using automated pre-programmed trading instructions accounting for variables such as time, price, and volume to send small slices of the order (child orders) out to the market over time. They were developed so that traders do not need to constantly watch a stock and repeatedly send those slices out manually.
Algorithmic composition: Algorithmic composition is the technique of using algorithms to create music. Algorithms have been used to compose music for centuries; the procedures used to plot voice-leading in Western counterpoint, for example, can often be reduced to algorithmic determinacy.
Algorithmic efficiency: In computer science, algorithmic efficiency is a property of an algorithm which relates to the number of computational resources used by the algorithm. An algorithm must be analyzed to determine its resource usage, and the efficiency of an algorithm can be measured based on usage of different resources.
Algorithms for calculating variance: Algorithms for calculating variance play a major role in computational statistics. A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.