RT Journal Article
T1 Analyzing animal escape data with circular nonparametric multimodal regression
A1 Alonso Pena, María
A1 Crujeiras Casais, Rosa María
K1 Multimodal regression
K1 Circular data
K1 Animal escape
AB Analyzing the escape direction of animals subject to covariates is a problem that requires statistical techniques beyond classical regression methods. Apart from the periodicity of the angle of direction, which demands the use of circular statistics, animal escape data usually call for the exploration of the preferred orientations rather than the expected orientation. In this paper we propose the use of a nonparametric method to estimate the conditional local modes of the escape directions of animals from a regression perspective. We present the estimation algorithms and study the asymptotic properties of the estimators as well as its finite sample performance through some simulation experiments. Our proposal is used to model the escape behavior of a group of larval zebrafish escaping from a robot predator. More broadly, the approach presented in this paper can be applied to many existing problems related to animal behavior or other fields.
PB Institute of Mathematical Statistics (IMS)
SN 1932-6157
YR 2023
FD 2023-03
LK https://hdl.handle.net/10347/43413
UL https://hdl.handle.net/10347/43413
LA eng
NO Alonso-Pena, M., Crujeiras, R.M (2023). Analyzing animal escape data with circular nonparametric multimodal regression. "Annals of Applied Statistics", vol. 17 , 1, 130 - 152.
NO CESGA
DS Minerva
RD 22 abr 2026