Absolute Error And Relative Error In Numerical Analysis Pdf

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Data: Errors in measurement or estimation of raw data Numerical Method: Errors based on some approximation. Representation of Numbers: for example, p cannot be represented exactly by a finite number of digits. Arithmetic: Mistakes in carrying out operations such as addition or multiplication.


The approximation error in some data is the discrepancy between an exact value and some approximation to it. An approximation error can occur because:. In the mathematical field of numerical analysis , the numerical stability of an algorithm indicates how the error is propagated by the algorithm. Given some value v and its approximation v approx , the absolute error is. In words, the absolute error is the magnitude of the difference between the exact value and the approximation. The relative error is the absolute error divided by the magnitude of the exact value.

This work develops a computational approach for boundary and initial-value problems by using operational matrices, in order to run an evolutive process in a Hilbert space. Besides, upper bounds for errors in the solutions and in their derivatives can be estimated providing accuracy measures. Differential equations are ubiquitous in engineering daily life but their solutions are sometimes very difficult, mainly if they are nonlinear. Several of them do not have an analytical solution describable by a finite combination of elementary functions, or even by an unlimited series with a determinable recurrence relation. In previous works, analytical and numerical results were obtained for nonlinear differential equations [ 1 — 3 ], and an algorithm called SIV Solving Initial Value was developed. Here, the problem of determining the error limits for SIV is emphasized, providing quality parameters for the method. In Section 2 , some general theoretical considerations about a numerical method for differential equations, by using expansions in Hilbert space, are presented.


This paper is concerned with the numerical solution of the general initial value problem for linear recurrence relations. An error analysis of direct recursion is given, based on relative rather than absolute error, and a theory of relative stability developed. Miller's algorithm for second order homogeneous relations is extended to more general cases, and the propagation of errors analysed in a similar manner. The practical significance of the theoretical results is indicated by applying them to particular classes of problem. This is a preview of subscription content, access via your institution.

Absolute Error

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Numerical Analysis - Errors

There are two techniques for measuring error: the absolute error of an approximation and the relative error of the approximation. The first gives how large the error is, while the second gives how large the error is relative to the correct value. Given an approximation a of a correct value x , we define the absolute value of the difference between the two values to be the absolute error.

The difference between the measured or inferred value of a quantity and its actual value , given by. The absolute error of the sum or difference of a number of quantities is less than or equal to the sum of their absolute errors. Abramowitz, M. New York: Dover, p. Weisstein, Eric W.

For example, is an approximation to with an absolute error of 1 and a relative error of 10−6, while 2 is an approximation to 1.

Approximation error

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Last Updated: March 15, References. This article was co-authored by our trained team of editors and researchers who validated it for accuracy and comprehensiveness. This article has been viewed , times. Learn more Absolute error is the actual amount you were off, or mistaken by, when measuring something. Relative error compares the absolute error against the size of the thing you were measuring. In order to calculate relative error, you must calculate the absolute error as well.

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