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Using image and curve registration for measuring the goodness of fit of spatial and temporal predictions

Using image and curve registration for measuring the goodness of fit of spatial and temporal predictions

Biometrics 60(4): 954-964

Conventional measures of model fit for indexed data (e.g., time series or spatial data) summarize errors in y, for instance by integrating (or summing) the squared difference between predicted and measured values over a range of x. We propose an approach which recognizes that errors can occur in the x-direction as well.

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Accession: 012731161

Download citation: RISBibTeXText

PMID: 15606416

DOI: 10.1111/j.0006-341x.2004.00251.x

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