A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts

This paper has a focus on non-stationary time series formed from small non-negative integer values which may contain many zeros and may be over-dispersed. It describes a study undertaken to compare various suitable adaptations of the simple exponential smoothing method of forecasting on a database of demand series for slow moving car parts. The methods considered include simple exponential smoothing with Poisson measurements, a finite sample version of simple exponential smoothing with negative binomial measurements, and the Croston method of forecasting. In the case of the Croston method, a maximum likelihood approach to estimating key quantities, such as the smoothing parameter, is proposed for the first time. The results from the study indicate that the Croston method does not forecast, on average, as well as the other two methods. It is also confirmed that a common fixed smoothing constant across all the car parts works better than maximum likelihood approaches.Count time series; forecasting; exponential smoothing; Poisson distribution; negative binomial distribution; Croston method.

‘Once a Local Surfer, Always a Local Surfer’: Local Surfing Careers in a Southwest English Village

This article reports on findings from an ethnographic study (2008–09) conducted in a village with a significant population of local surfers in Cornwall (Southwest England). Stimulated by Goffman's (1961) interpretation of the concept of career and elaborated by the work of Stebbins (1970) on “subjective career,” Stebbins's (1982) framework of “serious leisure” and “serious leisure career” (Stebbins, 2005), we identify moments from local surfer careers lived in this community setting. We suggest that similar to findings from other subcultural studies on sports careers the local surfing career in this context contains shared experiential stages: the nurtured stage, the possible competitive stage, the serious leisure traveller stage, the responsible stage, and the legends stage. We conclude that the shared experiences and pathways of a local surfing career can play a positive cultural role, not just for individuals but also for the construction and maintenance of local community life

The SoLid anti-neutrino detector's readout system

The SoLid collaboration have developed an intelligent readout system to reduce their 3200 silicon photomultiplier detector's data rate by a factor of 10000 whilst maintaining high efficiency for storing data from anti-neutrino interactions. The system employs an FPGA-level waveform characterisation to trigger on neutron signals. Following a trigger, data from a space time region of interest around the neutron will be read out using the IPbus protocol. In these proceedings the design of the readout system is explained and results showing the performance of a prototype version of the system are presented

Forecasting Compositional Time Series with Exponential Smoothing Methods

Compositional time series are formed from measurements of proportions that sum to one in each period of time. We might be interested in forecasting the proportion of home loans that have adjustable rates, the proportion of nonagricultural jobs in manufacturing, the proportion of a rock's geochemical composition that is a specific oxide, or the proportion of an election betting market choosing a particular candidate. A problem may involve many related time series of proportions. There could be several categories of nonagricultural jobs or several oxides in the geochemical composition of a rock that are of interest. In this paper we provide a statistical framework for forecasting these special kinds of time series. We build on the innovations state space framework underpinning the widely used methods of exponential smoothing. We couple this with a generalized logistic transformation to convert the measurements from the unit interval to the entire real line. The approach is illustrated with two applications: the proportion of new home loans in the U.S. that have adjustable rates; and four probabilities for specified candidates winning the 2008 democratic presidential nomination.compositional time series, innovations state space models, exponential smoothing, forecasting proportions

Modeling the mobility of living organisms in heterogeneous landscapes: Does memory improve foraging success?

Thanks to recent technological advances, it is now possible to track with an unprecedented precision and for long periods of time the movement patterns of many living organisms in their habitat. The increasing amount of data available on single trajectories offers the possibility of understanding how animals move and of testing basic movement models. Random walks have long represented the main description for micro-organisms and have also been useful to understand the foraging behaviour of large animals. Nevertheless, most vertebrates, in particular humans and other primates, rely on sophisticated cognitive tools such as spatial maps, episodic memory and travel cost discounting. These properties call for other modeling approaches of mobility patterns. We propose a foraging framework where a learning mobile agent uses a combination of memory-based and random steps. We investigate how advantageous it is to use memory for exploiting resources in heterogeneous and changing environments. An adequate balance of determinism and random exploration is found to maximize the foraging efficiency and to generate trajectories with an intricate spatio-temporal order. Based on this approach, we propose some tools for analysing the non-random nature of mobility patterns in general.Comment: 14 pages, 4 figures, improved discussio

Continental-scale patterns of pathogen prevalence: a case study on the corncrake

Pathogen infections can represent a substantial threat to wild populations, especially those already limited in size. To determine how much variation in the pathogens observed among fragmented populations is caused by ecological factors, one needs to examine systems where host genetic diversity is consistent among the populations, thus controlling for any potentially confounding genetic effects. Here, we report geographic variation in haemosporidian infection among European populations of corncrake. This species now occurs in fragmented populations, but there is little genetic structure and equally high levels of genetic diversity among these populations. We observed a longitudinal gradient of prevalence from western to Eastern Europe negatively correlated with national agricultural yield, but positively correlated with corncrake census population sizes when only the most widespread lineage is considered. This likely reveals a possible impact of local agriculture intensity, which reduced host population densities in Western Europe and, potentially, insect vector abundance, thus reducing the transmission of pathogens. We conclude that in the corncrake system, where metapopulation dynamics resulted in variations in local census population sizes, but not in the genetic impoverishment of these populations, anthropogenic activity has led to a reduction in host populations and pathogen prevalence