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Orbital position vector, orbital velocity vector, other orbital elements. In astrodynamics and celestial dynamics, the orbital state vectors (sometimes state vectors) of an orbit are Cartesian vectors of position and velocity that together with their time () uniquely determine the trajectory of the orbiting body in space.
Throughout this article, boldfaced unsubscripted and are used to refer to random vectors, and Roman subscripted and are used to refer to scalar random variables.. If the entries in the column vector = (,, …,) are random variables, each with finite variance and expected value, then the covariance matrix is the matrix whose (,) entry is the covariance [1]: 177 ...
A vector's components change scale inversely to changes in scale to the reference axes, and consequently a vector is called a contravariant tensor. A vector, which is an example of a contravariant tensor, has components that transform inversely to the transformation of the reference axes, (with example transformations including rotation and ...
The covariance matrix of an random vector is an matrix whose (,) th element is the covariance between the i th and the j th random variables. [ 2 ] : p.372 Unlike in the case of real random variables, the covariance between two random variables involves the complex conjugate of one of the two.
August 2008) (Learn how and when to remove this message) In probability theory , the multidimensional Chebyshev's inequality [ 1 ] is a generalization of Chebyshev's inequality , which puts a bound on the probability of the event that a random variable differs from its expected value by more than a specified amount.
The covariance matrix is the expected value, element by element, of the matrix computed as [ []] [ []], where the superscript T refers to the transpose of the indicated vector: [2]: p. 464 [3]: p.335
The sample covariance matrix (SCM) is an unbiased and efficient estimator of the covariance matrix if the space of covariance matrices is viewed as an extrinsic convex cone in R p×p; however, measured using the intrinsic geometry of positive-definite matrices, the SCM is a biased and inefficient estimator. [1]
The term 'general covariance' was used in the early formulation of general relativity, but the principle is now often referred to as 'diffeomorphism covariance'. Diffeomorphism covariance is not the defining feature of general relativity, [1] and controversies remain regarding its present status in general relativity.