The SPWMC analysis with bounded power-law, red, pure power-law, green, and bounded exponential, blue, for moves (**A**) and pauses (**B**). A value of weighted Akaike information criteria (wAIC) of one gives the maximum weight of evidence in favour of the models. The results here are means for all individuals. Error bars indicate +/− one SD. The probability density functions (**C**) and the complementary cumulative distribution plots (**D**) and for moves, blue, and pauses, red, showing the empirical data and the model fits for the power law with a stretched exponential tail model (black line). μ is the scaling parameter of the power-law, β is a parameter that tells us the deviation of the tail from an exponential. For moves: μ = 1.49, β = 0.55; for pauses: μ = 1.67, β = 0.23. (**E–F**) shows the observed and expected distributions for moves and pauses. Log-log plot of the frequency distribution of different move (**E**) and pause lengths (**F**). Open circles show the observed distribution from our data and dots show the expected distribution from the model fit (a power-law with a stretched exponential tail model). We assume a Poisson distribution for the deviations from the expected values for each bin. The black error bars show +/−2 SD from our expected value.

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