ABSTRACT
Animal telemetry data usually consist of time-indexed spatial locations, and can be thought of as multivariate time series. Thus, a foundation in the statistical treatment of time series data is important for modeling animal movement. This chapter provides a useful set of tools and concepts that one may wish to apply to telemetry data. It reviews time series by introducing notation and terminology in the univariate context and then move to the multivariate context. The essential premise in statistics for time series involves the assessment and modeling of dependence in temporally indexed data and processes. The covariance function for time series is the analog to the covariogram in spatial statistics and the stationarity assumption has a similar interpretation as well; specifically, that the temporal process behaves according to the same dependence throughout the entire time series.
