In a recent article the authors inferred classical composer similarities on the basis of their common and distinct personal (individual) musical influences. In this paper, the authors examine how much, if any, additional explanation can be added when ‘ecological’ measures (i.e., other characteristics such as time period, geographical location, school association, instrumentation emphases, etc.) are also taken into account. Although the two methods do not generate identical similarities rankings, their combination does provide, arguably, an improved system of ranking.
CheethamA. H.HazelJ. E. (1969) Binary (presence-absence) similarity coefficients. Journal of Paleontology43: 1130–1136. doi:10.2307/1302424.
2.
GathererD. (1997) The evolution of music – A comparison of Darwinian and dialectical methods. Journal of Social and Evolutionary Systems20: 75–92. doi:10.1016/S1061-7361(97)90030-8.
3.
HayekL.-A. C. (1994) Analysis of amphibian biodiversity data. In: HeyerW. R.DonnellyM. A.McDiarmidR. W.HayekL.-A. C.FosterM. S. (eds) Measuring and monitoring biological diversity: Standard methods for amphibians, Washington, DC: Smithsonian Books, pp. 207–269.
4.
JaccardP. (1901) Étude comparative de la distribution florale dans une portion des Alpes et du Jura. Bull. de la Societé Vaudoise des Sciences Naturelles37: 547–579.
5.
LinquistS. (2010) The evolution of culture, Burlington, VT: Ashgate.
6.
PotthoffR. F.WhittinghillM. (1966) Testing for homogeneity. I. The binomial and multinomial distributions. Biometrika53: 167–182. doi:10.1093/biomet/53.1-2.167.
7.
SmithC. H. (1983) A system of world mammal faunal regions. I. Logical and statistical derivation of the regions. Journal of Biogeography10: 455–466.
SmithC. H.GeorgesP. (2014) Composer similarities through “The Classical Music Navigator”: Similarity inference from composer influences. Empirical Studies of the Arts32(2): 205–229.
