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We use the spaces A ( p ) as the measure of approximation.
We use the spaces of multiple absolute summable sequences as the measure of approximation.
Z. Krasniqi (Acta Comment. Univ. Tartu Math. 17:89–101, 2013) and the authors (Acta Comment. Univ. Tartu Math. 13:11–20092009; Proc. Est. Acad. Sci. 67:50–60, 2018) to the case when considered function is (2pi/r -periodic and the measure of approximation depends on r-differences of the entries of the considered matrices.
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When they are not independent, the possible "contradiction" serves as a measure of the approximation of the solution.
The law of large numbers, however, does not provide a measure of the approximation error which is usually of more interest to practitioners.
We arrange the rest of the article as follows: First, we introduce the asymptotic logarithmic likelihood ratio as a measure of Markov approximation of the arbitrary random field on a homogeneous tree.
So aiming for truth, as opposed to warrant, does not point to a possible line of action, just as we have no measure of our approximation to truth other than increasing warrant.
We use the spaces A ( p ) to measure the 'degree of approximation'.
To measure the accuracy of approximation formula 2 π n ( n / e ) n e M n [ m ], define the sequence (w n )n≥1by the relation n !
Unlike previous studies, Lu and Park [26] first studied the stability of two types of additive set-valued functional equations, in which the inclusion relation is employed to measure the degree of approximation.
The RMSEA is an indication of model fit and is based on the population discrepancy function, which is a standardized measure of error of approximation [ 36].
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