Receiver function inversion by trans‐dimensional Monte Carlo sampling

By N. Agostinetti, Alberto Malinverno. 2010

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Transdimensional tomography with unknown data noise (2012, background): “In the last decade, transdimensional inversion has become popular in Earth sciences and has been applied to a wide range of areas (e.g. Malinverno 2002; Stephenson et al. 2004, 2006; Jasra et al. 2006; Hopcroft et al. 2009; Charvin et al. 2009; Gallagher et al. 2011; Dettmer et al. 2010; Luo 2010; P”
Transdimensional inversion of receiver functions and surface wave dispersion (2012, methodology): “[46] This “ensemble solution” contains many models with variable parameterization, and inference can be carried out with ensemble averages over the structure [see Piana Agostinetti and Malinverno, 2010].”
Receiver function deconvolution using transdimensional hierarchical Bayesian inference (2014, methodology): “Motivated by the work of Piana Agostinetti & Malinverno (2010), who used RJMCMC to infer velocity structure from receiver functions, we treat the number of parameters defining the receiver function as an unknown to be estimated in the inversion.”