Many species of hermit crabs, such as Calcinus and Clibanarius spp., live on rocky shores in tropical and warm temperate regions. During low tide, some of these species climb out of tidal pools onto exposed rock surfaces with their shell-aperture directed upwards. However, the adaptive significance of the ‘air-exposure (AE) behaviour’ was only previously investigated in several Clibanarius species; this behaviour is hypothesised to prevent competition for shells in tide pools during low tide. Considering the lack of knowledge of Calcinus species, understanding their significance is necessary to elucidate the ecological or evolutionary and general adaptive significance of AE behaviour in hermit crabs. The AE behaviour of Ca. laevimanus, which is the dominant species in sub-tropical and tropical rocky shores, was investigated on the rocky shores of Naze, Amami, Kagoshima, Japan. The generalised linear model indicated a significant positive effect of the gastropod shell length on the occurrences of this AE behaviour. Therefore, the current result indicates that individuals with larger gastropod shells, which offer them the potential to grow to larger sizes, more frequently engage in AE behaviour during low tides. The present result supports the previous hypothesis but suggests that external factor (i.e. shell size)-dependent AE behaviour has evolved in Calcinus species, which differs from the internal factor (i.e. body size or sex)-dependent AE behaviour in Clibanarius species.

Semecarpus calcicola is an endangered tree restricted to Pulau Mantanani, Malaysia. New data of population size and structure was used to reassess the IUCN threat category of this species. Results are based on twenty-six 400 m2 plots in a 26.5 ha area that included the majority of Semecarpus calcicola’s known population. GLMs were used to investigate the relationship between the number of individuals and elevation. Estimates of the population size for each size class were determined using Horvitz-Thompson estimators, generalised regression estimators and spatial linear models and extrapolated to the study area. Elevations of the plots were obtained from a digital elevation model as auxiliary data. Significant relationships were found between the number of individuals and elevation. Mature individuals are more common at higher elevations, whilst seedlings, saplings and poles are more abundant in the lower elevation plots. Land-use change due to the increase of tourism activities and the local community drives the significant decreases of mature individuals within the lower elevation. Introduced cattle, tourism-related land-use change and plantation activities further threaten the population of S. calcicola, particularly smaller individuals due to herbivory. The estimate of population size varied among the methods and size classes. The estimated number of mature individuals ranged from 509 to 764.

Psychosocial stimulation is one of the recommended interventions in the management of hospitalised children with severe acute malnutrition (SAM). However, there is currently limited scientific evidence supporting the effectiveness of the intervention. The study aimed to examine the effects of psychosocial stimulation on the development, nutrition, and treatment outcomes of hospitalised SAM children. A cluster-randomised controlled trial was conducted among health facilities that provide inpatient care for children with SAM in Silti Zone, Ethiopia. Fifty-eight children enrolled in the intervention facilities were provided stimulation intervention during their inpatient care and for 6 months after discharge. Sixty-eight children enrolled from control health facilities received routine inpatient care without stimulation and were followed for six months. Health education was provided to all caregivers on child health-related topics. Child development and nutrition outcomes were assessed four times using Denver II-Jimma and anthropometric measurements while the length of hospitalisation was used to measure treatment outcome. Children in the intervention group showed significantly better scores in Personal Social (p=0.001, effect size=0.77), Fine Motor (p=0.001, effect size=1.87), and Gross Motor (p=0.001, effect size=0.78) developmental domains from baseline to end line. Language domain however showed a significant difference only after discharge and intervention children scored better at six months (p<0.001, effect size=0.59). The intervention significantly improved treatment outcomes (p=0.010), but no significant changes in nutritional outcomes were documented. The findings highlighted the benefits of the intervention and the need to promote these interventions in health facilities within resource-limited settings.

The mvClaim package in R provides flexible modelling frameworks for multivariate insurance claim severity modelling. The current version of the package implements a parsimonious mixture of experts (MoE) model family with bivariate gamma distributions, as introduced in Hu et al., and a finite mixture of copula regressions within the MoE framework as in Hu & O’Hagan. This paper presents the modelling approach theory briefly and the usage of the models in the package in detail. This package is hosted on GitHub at https://github.com/senhu/.

This paper adopts an actuarial approach to identify the risk factors of government-funded maternal out-of-hospital costs in Australia, with a focus on women who experience adverse birth outcomes. We use a two-phase modelling methodology incorporating both classification and regression trees and generalised linear models on a data set that links administrative and longitudinal survey data from a large sample of women, to address maternal out-of-hospital costs. We find that adverse births are a statistically significant risk factor of out-of-hospital costs in both the delivery and postnatal periods. Furthermore, other significant cost risk factors are in-vitro fertilisation, specialist use, general practitioner use, area of residence and mental health factors (including anxiety, intense anxiety, postnatal depression and stress about own health) and the results vary by perinatal sub-period and the patient’s private health insurance status. We highlight these differences and use the results as an evidence base to inform public policy. Mental health policy is identified as a priority area for further investigation due to the dominance of these factors in many of the fitted models.

This paper considers a wide range of stochastic reserving models for use in general insurance, beginning with stochastic models which reproduce the traditional chain-ladder reserve estimates. The models are extended to consider parametric curves and smoothing models for the shape of the development run-off, which allow extrapolation for the estimation of tail factors. The Bornhuetter-Ferguson technique is also considered, within a Bayesian framework, which allows expert opinion to be used to provide prior estimates of ultimate claims. The primary advantage of stochastic reserving models is the availability of measures of precision of reserve estimates, and in this respect, attention is focused on the root mean squared error of prediction (prediction error). Of greater interest is a full predictive distribution of possible reserve outcomes, and different methods of obtaining that distribution are described. The techniques are illustrated with examples throughout, and the wider issues discussed, in particular, the concept of a ‘best estimate’; reporting the variability of claims reserves; and use in dynamic financial analysis models.

This paper extends the methods introduced in England & Verrall (2002), and shows how predictive distributions of outstanding liabilities in general insurance can be obtained using bootstrap or Bayesian techniques for clearly defined statistical models. A general procedure for bootstrapping is described, by extending the methods introduced in England & Verrall (1999), England (2002) and Pinheiro et al. (2003). The analogous Bayesian estimation procedure is implemented using Markov-chain Monte Carlo methods, where the models are constructed as Bayesian generalised linear models using the approach described by Dellaportas & Smith (1993). In particular, this paper describes a way of obtaining a predictive distribution from recursive claims reserving models, including the well known model introduced by Mack (1993). Mack's model is useful, since it can be used with data sets which exhibit negative incremental amounts. The techniques are illustrated with examples, and the resulting predictive distributions from both the bootstrap and Bayesian methods are compared.

A simple upper bound for the variance of the frequency estimates in a multivariate tariff using class criteria is deduced. This upper bound is based exclusively on univariate statistics and can, therefore, be calculated before a GLM analysis is carried out. It can be used to estimate the number of claims that will be needed for a tariff calculation depending on the number of tariff criteria and the number of levels of each criterion.

The article is a revised version of a paper presented at the XXXIst ASTIN Colloquium in Porto Cervo.

The three annual 2¼% interest coupons of the Winterthur Insurance convertible bond (face value Chf 4 700) will only be paid out if during their corresponding observation periods no major storm or hail storm on one single day damages at least 6 000 motor vehicles insured with Winterthur Insurance. Data for events, where storm or hail damaged more than 1 000 insured vehicles, are available for the last ten years. Using a constant-parameter model, the estimated discounted value of the three Wincat coupons together is Chf 263.29. A conservative evaluation, which accounts for the standard deviation of the estimate, gives a coupon value of Chf 238.25. However, fitting models which admit a trend or a change-point, leads to substantially higher knock-out probabilities of the coupons. The estimated discounted values of the coupons can drop below the above conservative value; a conservative evaluation as above leads to substantially lower values. Hence, already the model uncertainty is higher than the standard deviations of the used estimators. This shows the dominance of the model risk. Consistency, dispersion, robustness and sensitivity of the models are analysed by a simulation study.