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Max-mixture processes are defined as Z = max(aX, (1 -- a)Y) with X anasymptotic dependent (AD) process, Y an asymptotic independent (AI) process anda $\in$ [0, 1]. So that, the mixing coefficient a may reveal the strength ofthe AD part present in the max-mixture process. In this paper we focus on twotests based on censored pairwise likelihood estimates. We compare theirperformance through an extensive simulation study. Monte Carlo simulation playsa fundamental tool for asymptotic variance calculations. We apply our tests todaily precipitations from the East of Australia. Drawbacks and possibledevelopments are discussed.

Censored pairwise likelihood-based tests for mixing coefficient of spatial max-mixture models