The concept of the variance estimation for the neural network approximator by jackknife subsampling

Jacek Pietraszek,

Aneta Gądek-Moszczak

Abstrakt

The estimation of a variance for a semi-parametric neural network model variance for geometric properties of sintered metal will be done on the basis of jackknife subsampling method. Calculation results are of great practical significance because it will be possible to use proposed approach in similar microscale modelling. The proposed approach is simple and has many advantages if model identification procedure is computational expensive.

Słowa kluczowe: jackknife variance estimation, statistical methods, image analysis, error estimate, metal powder sintering
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