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Roundness is the measure of how closely the shape of an object approaches that of a mathematically perfect circle.Roundness applies in two dimensions, such as the cross sectional circles along a cylindrical object such as a shaft or a cylindrical roller for a bearing.
In mathematics and statistics, a circular mean or angular mean is a mean designed for angles and similar cyclic quantities, such as times of day, and fractional parts of real numbers. This is necessary since most of the usual means may not be appropriate on angle-like quantities.
However, it also blocks one standard definition of the natural numbers. First, we define a property as being "hereditary" if, whenever a number n has the property, so does n +1. Then we say that x has the property of being a natural number if and only if it has every hereditary property that 0 has. This definition is blocked, because it defines ...
The usefulness of the von Mises distribution is twofold: it is the most mathematically tractable of all circular distributions, allowing simpler statistical analysis, and it is a close approximation to the wrapped normal distribution, which, analogously to the linear normal distribution, is important because it is the limiting case for the sum ...
Given a number base , a natural number with digits is an automorphic number if is a fixed point of the polynomial function = over /, the ring of integers modulo.As the inverse limit of / is , the ring of -adic integers, automorphic numbers are used to find the numerical representations of the fixed points of () = over .
In statistics, circular analysis is the selection of the details of a data analysis using the data that is being analysed. It is often referred to as double dipping, as one uses the same data twice.
The von Mises probability density function for the angle x is given by: [2] (,) = ( ()) ()where I 0 is the modified Bessel function of the first kind of order 0, with this scaling constant chosen so that the distribution sums to unity: () = ().
The usefulness of the von Mises distribution is twofold: it is the most mathematically tractable of all circular distributions, allowing simpler statistical analysis, and it is a close approximation to the wrapped normal distribution, which, analogously to the linear normal distribution, is important because it is the limiting case for the sum ...