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Directional statistics (also circular statistics or spherical statistics) is the subdiscipline of statistics that deals with directions (unit vectors in Euclidean space, R n), axes (lines through the origin in R n) or rotations in R n. More generally, directional statistics deals with observations on compact Riemannian manifolds including the ...
In probability theory and directional statistics, the von Mises distribution (also known as the circular normal distribution or the Tikhonov distribution) is a continuous probability distribution on the circle. It is a close approximation to the wrapped normal distribution, which is the circular analogue of the normal distribution.
Circular bivariate normal distribution 20 hits distribution example. The original concept of CEP was based on a circular bivariate normal distribution (CBN) with CEP as a parameter of the CBN just as μ and σ are parameters of the normal distribution.
The circular standard deviation, which is a useful measure of dispersion for the wrapped normal distribution and its close relative, the von Mises distribution is given by: s = ln ( R − 2 ) 1 / 2 = σ {\displaystyle s=\ln(R^{-2})^{1/2}=\sigma }
a test for periodicity in irregularly sampled data, [1] a derivation of the above to test for non-uniformity (as unimodal clustering) of a set of points on a circle (e.g. compass directions), [ 2 ] sometimes known as the Rayleigh z test.
In probability and statistics, a circular distribution or polar distribution is a probability distribution of a random variable whose values are angles, usually taken to be in the range [0, 2π). [1] A circular distribution is often a continuous probability distribution , and hence has a probability density , but such distributions can also be ...
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.
A 10,000 point Monte Carlo simulation of the distribution of the sample mean of a circular uniform distribution for N = 3 Probability densities (¯) for small values of . Densities for N > 3 {\displaystyle N>3} are normalised to the maximum density, those for N = 1 {\displaystyle N=1} and 2 {\displaystyle 2} are scaled to aid visibility.