No abstract

Non‐parametric estimation and bootstrap techniques play an important role in many areas of Statistics. In the point process context, kernel intensity estimation has been limited to exploratory analysis because of its inconsistency, and some consistent alternatives have been proposed. Furthermore, most authors have considered kernel intensity estimators with scalar bandwidths, which can be very restrictive. This work focuses on a consistent kernel intensity estimator with unconstrained bandwidth matrix. We propose a smooth bootstrap for inhomogeneous spatial point processes. The consistency of the bootstrap mean integrated squared error (MISE) as an estimator of the MISE of the consistent kernel intensity estimator proves the validity of the resampling procedure. Finally, we propose a plug‐in bandwidth selection procedure based on the bootstrap MISE and compare its performance with several methods currently used through both as a simulation study and an application to the spatial pattern of wildfires registered in Galicia (Spain) during 2006.

Abstract. Self-thinning (ST) models have been widely used in the last decades to describe population dynamics under intraspecific competition in plant and animal communities. Nevertheless, their applicability in animal populations is subjected to the appropriate inclusion of space occupancy and energy requirements. Specifically, the disposition of gregarious sessile animals in complex matrices hampers the application of classical ST models. This paper reviews the self-thinning models, regression methods (central tendency and frontier techniques) and discrimination criteria currently applied for gregarious sessile species through application to the analysis of mussel populations (Mytilus galloprovincialis) grown in suspended culture. In addition, we propose to model the temporal evolution of site occupancy in the stochastic frontier function (SFF). Our results confirm that the number of layers should be included in the classical bidimensional ST model for the analysis of multilayered populations. The estimated parameters obtained by the different fitting techniques depended on the measurement method of the variables in the model. This, together with the proximity between the space and food selfthinning theoretical exponents (SST and FST, respectively) highlights the difficulty in discriminating the competition limiting factor (space/food) from the self-thinning exponent. On the other hand, the SFF provided congruent results for biomass and individual mass analysis, in contrast to the lack of robustness observed for the central tendency regression methods. Furthermore, the SFF approach allowed a dynamic interpretation of the ST process providing insight into the temporal evolution of site occupancy. These results highlight the suitability of the stochastic frontier approach in the analysis of self-thinning dynamics in sessile animal populations.