Archive
B02: Mini-workshop: Mathematical modeling and statistical analysis of cultural datasets (Jan. 8-9, 2020)
Schedule：Jan. 8-9th, 2020
Venue: Room: 603 (6th floor), Nakano Campus, Meiji University, Tokyo, Japan
Supported by: PaleoAsia project B02 (mathematical modelling) group
Organizer: Joe Yuichiro Wakano (Meiji Univ., Integrated Mathematical Sciences)
Invited speakers:
Luke Premo (Washington State Univ., Anthropology)
Enrico Crema (Univ. of Cambridge, Archaeology)
OBJECTIVE
Mathematical modeling and statistical analysis of empirical datasets are receiving more and more attention in related fields. Such theoretical studies shall provide generalized understanding of cultural origin and its diversity in Asia during Paleolithic, which is also the goal of the PaleoAsia project. Participants as well as speakers are expected to communicate with each other in a mini-workshop style through active discussion.
PROGRAM
8th January (Wed)
13:00 Opening
13:10 Plenary talk 1
Enrico Crema (Univ. of Cambridge, Archaeology)
“Confessions of an Archaeologist:
Inferential Challenges in Reconstructing Transmission Processes from Object”
60min.
14:10
Kohei Tamura (Tohoku Univ)
“A Quantitative Analysis of PaleoAsiaDB”
40min.
14:50 – 15:20 break
15:20 General discussion 1
How we deal with noisy dataset (e.g., coding error, missing data)?
How we deal with data not at equilibrium?
around 5:30pm, workshop dinner
9th January (Thu)
10:00 Plenary talk 2
Luke Premo (Washington State Univ., Anthropology)
“Investigating how time-averaging affects assemblage-level variation in
continuous and discrete cultural traits”
90min.
12:00
Mitsuhiro Nakamura (Meiji Univ)
“An information-theoretic approach to cultural variation”
40min.
12:40 – 14:20 lunch break
14:20
Joe Yuichiro Wakano (Meiji Univ., Integrated Mathematical Sciences)
“Diffusion approximation of cultural popularity spectrum”
40 min.
15:00
Kenichi Aoki (Meiji Univ)
“A three-population wave-of-advance model for the European early Neolithic:
revising the Aoki et al. (1996) model to be qualitatively consistent with the ancient DNA data”
40min.
15:40 – 16:00 break
16:00 General discussion 2
Difference between snapshot data and time-averaged data
How we detect/deal with correlated cultural elements?
17:00 Closing