• Boreal rodents fluctuating in space and time: Tying the observation process to the modeling of seasonal population dynamics 

      Nicolau, Pedro Guilherme (Doctoral thesis; Doktorgradsavhandling, 2022-06-03)
      Small rodents are some of the most important elements of boreal/arctic food webs, where they play essential functional roles. Their population dynamics are characterized by large amplitude multi-annual cycles regulated by direct and delayed density-dependence. These drastic variations in abundance have deep cascading effects into the whole ecosystem. Hence, the study boreal rodent population processes ...
    • Finite-sample properties of estimators for first and second order autoregressive processes 

      Sørbye, Sigrunn Holbek; Nicolau, Pedro Guilherme; Rue, Håvard (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-05)
      The class of autoregressive (AR) processes is extensively used to model temporal dependence in observed time series. Such models are easily available and routinely fitted using freely available statistical software like R. A potential problem is that commonly applied estimators for the coefficients of AR processes are severely biased when the time series are short. This paper studies the ...
    • Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data 

      Nicolau, Pedro Guilherme; Sørbye, Sigrunn Holbek; Yoccoz, Nigel (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-31)
      Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true ...