144 E. Klinger and J. Hasenauer
- Moral, P.D., Doucet, A., Jasra, A.: An adaptive Sequential Monte Carlo method
for Approximate Bayesian Computation. Stat. Comput. 22 (5), 1009–1020 (2012) - Nunes, M.A., Balding, D.J.: On optimal selection of summary statistics for approx-
imate bayesian computation. Stat. Appl. Genet. Mol. Biol. 9 (1), 34 (2010). doi:10.
2202/1544-6115.1576 - Prusiner, S.B.: Novel proteinaceous infectious particles cause Scrapie. Science
216 (4542), 136–144 (1982) - Salgado-Ugarte, I.H., Perez-Hernandez, M.A.: Exploring the use of variable band-
width kernel density estimators. Stata J. 3 (2), 133–147 (2003) - Silk, D., Filippi, S., Stumpf, M.P.H.: Optimizing threshold-schedules for sequen-
tial Approximate Bayesian Computation: applications to molecular systems. Stat.
Appl. Genet. Mol. Biol. 12 (5), 603–618 (2013) - Silverman, B.W.: Density Estimation for Statistics and Data Analysis, vol. 26.
CRC Press, Boca Raton (1986) - Sisson, S.A., Fan, Y., Tanaka, M.M.: Sequential Monte Carlo without likelihoods.
Proc. Natl. Acad. Sci. 104 (6), 1760–1765 (2007) - de Souza, L.G.M., Haida, H., Th ́evenin, D., Seidel-Morgenstern, A., Janiga, G.:
Model selection and parameter estimation for chemical reactions using global model
structure. Comput. Chem. Eng. 58 , 269–277 (2013) - Sunn ̊aker, M., Busetto, A.G., Numminen, E., Corander, J., Foll, M., Dessimoz, C.:
Approximate Bayesian Computation. PLOS Comput. Biol. 9 (1), e1002803 (2013) - Toni, T., Stumpf, M.P.H.: Simulation-based model selection for dynamical systems
in systems and population biology. Bioinformatics 26 (1), 104–110 (2010) - Toni, T., Welch, D., Strelkowa, N., Ipsen, A., Stumpf, M.P.H.: Approximate
Bayesian Computation scheme for parameter inference and model selection in
dynamicalsystems.J.Roy.Soc.Interface 6 (31), 187–202 (2009) - Westerhuis, J.A., Boelens, H.F.M., Iron, D., Rothenberg, G.: Model selection and
optimal sampling in high-throughput experimentation. Anal. Chem. 76 (11), 3171–
3178 (2004)