To accurately model finger input, we propose a dualdistribution
hypothesis
to interpret the distribution of
endpoints of finger input. We hypothesize that the endpoint
distribution is a sum of two independent normal
distributions. One reflects the relative touch precision
governed by the speed-accuracy tradeoff in the human
motor system, and the other reflects the absolute precision
of finger touch independent of the speed-accuracy tradeoff
effect.