In this paper, we combine polynomial functions, Generalized Estimating Equations, and bootstrap-based model selection to test for signatures of linear or nonlinear relationships between body surface temperature and am...In this paper, we combine polynomial functions, Generalized Estimating Equations, and bootstrap-based model selection to test for signatures of linear or nonlinear relationships between body surface temperature and ambient temperature in endotherms. Linearity or nonlinearity is associated with the absence or presence of cutaneous vasodilation and vasoconstriction, respectively. We obtained experimental data on body surface temperature variation from a mammalian model organism as a function of ambient temperature using infrared thermal imaging. The statistical framework of model estimation and selection successfully detected linear and nonlinear relationships between body surface temperature and ambient temperature for different body regions of the model organism. These results demonstrate that our statistical approach is instrumental to assess the complexity of thermoregulation in endotherms.展开更多
文摘In this paper, we combine polynomial functions, Generalized Estimating Equations, and bootstrap-based model selection to test for signatures of linear or nonlinear relationships between body surface temperature and ambient temperature in endotherms. Linearity or nonlinearity is associated with the absence or presence of cutaneous vasodilation and vasoconstriction, respectively. We obtained experimental data on body surface temperature variation from a mammalian model organism as a function of ambient temperature using infrared thermal imaging. The statistical framework of model estimation and selection successfully detected linear and nonlinear relationships between body surface temperature and ambient temperature for different body regions of the model organism. These results demonstrate that our statistical approach is instrumental to assess the complexity of thermoregulation in endotherms.
