Remark. The theorem can also be proven by the method given in [12] in Definition. We say that an interpolation scheme Remarks. 1. In the uni-dimensional case, the Pólya condition is equivalent

regularity 106 Since L S L S \ + = , we get L S E \ L S \ ≤ and then, by 3, L E L ≥ , which proves the theorem. □ 13. Remark. The theorem can also be proven by the method given in [12] in the case where S is a lower set with respect to d IN . For the case of lower sets, the theorem above is known under the Polya condition. Accordingly, we introduce the following terminology:

14. Definition. We say that an interpolation scheme

, , E S Z or an incidence matrix E satisfies the Polya condition if L E L ≥ , for all sets L which are lower with respect to S d IN S L ⊂ ⊂ .

15. Remarks. 1. In the uni-dimensional case, the Pólya condition is equivalent

to the almost regularity of the scheme: a scheme is almost regular if and only if it satisfies the Polya condition cf. [12], theorem 2.2.5. In the multidimensional case this is not longer true. Nevertheless, there are particular classes of interpolation schemes for which the Pólya condition is equivalent to the almost regularity actually there are classes for which the normality of the scheme is equivalent to the almost regularity see e.g. theorem 19 below. 2. A restatement of the previous theorem says that an interpolation scheme whose incidence matrix does not satisfy the Pólya condition cannot be almost regular. This is very useful in practice when we try to construct interpolation schemes that are almost regular or regular. Hence the theorem, and the Pólya condition, give us lower bounds for the numbers of interpolations that are necessary on the derivatives P , so that the almost regularity of the scheme is not spoiled. Next, we are looking for conditions for almost regularity which do not lower the number of nodes or the number of derivatives in the interpolation problem. Such a condition is presented in the next theorem. Although this theorem is a consequence of the Pólya condition, it does give a criteria which bounds the numbers of interpolations of a given order for the derivatives depending on the dimension of the space of derivatives of the given order. Of course, when we are trying to construct regular interpolation schemes, such conditions are easy to check.

16. Theorem. If

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