Estimation of parametric and nonparametric models for univariate claim severity distributions - an approach using R

This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Participation of interleukin-5, interleukin-8 and leukotriene B4 in eosinophil accumulation in two different experimental models

There are several experimental models describing in vivo eosinophil (EO) migration, including ip injection of a large volume of saline (SAL) or Sephadex beads (SEP). The aim of this study was to investigate the mechanisms involved in the EO migration in these two models. Two consecutive injections of SAL given 48 hr apart, induced a selective recruitment of EO into peritoneal cavity of rats, which peaked 48 hr after the last injection. SEP, when injected ip, promoted EO accumulation in rats. The phenomenom was dose-related and peaked 48 hr after SEP injection. To investigate the mediators involved in this process we showed that BW A4C, MK 886 and dexamethasone (DXA) inhibited the EO migration induced by SAL and SEP. To investigate the source of the EO chemotactic factor we showed that mast cells, macrophages (MO), but not lymphocytes, incubated in vitro in presence of SAL released a factor which induced EO migration. With SEP, only mast cells release a factor that induced EO migration, which was inhibited by BW A4C, MK 886 and DXA. Furthermore, the chemotactic activity of SAL-stimulated mast cells was inhibited by antisera against IL-5 and IL-8 (interleukin). SAL-stimulated MO were only inhibited by anti-IL-8 antibodies as well SEP-stimulated mast cells. These results suggest that the EO migration induced by SAL may be dependent on resident mast cells and MO and mediated by LTB4, IL-5 and IL-8. SEP-induced EO migration was dependent on mast cells and may be mediated by LTB4 and IL-8. Furthermore, IL-5 and IL-8 induced EO migration, which was also dependent on resident cells and mediated by LTB4 . In conclusion, EO migration induced by SAL is dependent on mast cells and MO, whereas that induced by SEP is dependent on mast cells alone. Stimulated mast cells release LTB4, IL-5 and IL-8 while MO release LTB4 and IL-8. The IL-5 and IL-8 release by the SAL or SEP-stimulated resident cells may act in an autocrine fashion, thus potentiating LTB4 release.

Role of eosinophilic airway inflammation in models of asthma

Eosinophils play a central role in the establishment and outcome of bronchial inflammation in asthma. Animal models of allergy are useful to answer questions related to mechanisms of allergic inflammation. We have used models of sensitized and boosted guinea pigs to investigate the nature of bronchial inflammation in allergic conditions. These animals develop marked bronchial infiltration composed mainly of CD4+ T-lymphocytes and eosinophils. Further provocation with antigen leads to degranulation of eosinophils and ulceration of the bronchial mucosa. Eosinophils are the first cells to increase in numbers in the mucosa after antigen challenge and depend on the expression of alpha 4 integrin to adhere to the vascular endothelium and transmigrate to the mucosa. Blockage of alpha4 integrin expression with specific antibody prevents not only the transmigration of eosinophils but also the development of bronchial hyperresponsiveness (BHR) to agonists in sensitized and challenged animals, clearly suggesting a role for this cell type in this altered functional state. Moreover, introduction of antibody against Major Basic Protein into the airways also prevents the development of BHR in similar model. BHR can also be suppressed by the use of FK506, an immunosuppressor that reduces in almost 100% the infiltration of eosinophils into the bronchi of allergic animals. These data support the concept that eosinophil is the most important pro-inflammatory factor in bronchial inflammation associated with allergy.

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

Climate-based empirical models show biased predictions of butterfly communities along environmental gradients

A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.

Stochastic time-concentration activity models for cytotoxicity in 3D brain cell cultures.

BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.

A non-possibility theorem for joint-stability in interindustry models

Joint-stability in interindustry models relates to the mutual simultaneous consistency of the demand-driven and supply-driven models of Leontief and Ghosh, respectively. Previous work has claimed joint-stability to be an acceptable assumption from the empirical viewpoint, provided only small changes in exogenous variables are considered. We show in this note, however, that the issue has deeper theoretical roots and offer an analytical demonstration that shows the impossibility of consistency between demand-driven and supply-driven models.

Entrevistant infants pre-escolars víctimes d’abús sexual i/o maltractament familiar : Eficàcia dels models d’entrevista forense

Entrevistant infants pre-escolars víctimes d’abús sexual i/o maltractament familiar: eficàcia dels models d’entrevista forense Entrevistar infants en edat preescolar que han viscut una situació traumàtica és una tasca complexa que dins l’avaluació psicològica forense necessita d’un protocol perfectament delimitat, clar i temporalitzat. Per això, s’han seleccionat 3 protocols d’entrevista: el Protocol de Menors (PM) de Bull i Birch, el model del National Institute for Children Development (NICHD) de Michel Lamb, a partir del qual es va desenvolupar l’EASI (Evaluación del Abuso Sexual Infantojuvenil) i l’Entrevista Cognitiva (EC) de Fisher i Geiselman. La hipòtesi de partida vol comprovar si els anteriors models permeten obtenir volums informatius diferents en infants preescolars. Conseqüentment, els objectius han estat determinar quin dels models d’entrevista permet obtenir un volum informatiu amb més precisions i menys errors, dissenyar un model d’entrevista propi i consensuar aquest model. En el treball s’afegeixen esquemes pràctics que facilitin l’obertura, desenvolupament i tancament de l’entrevista forense. La metodologia ha reproduït el binomi infant - esdeveniment traumàtic, mitjançant la visualització i l’explicació d’un fet emocionalment significatiu amb facilitat per identificar-se: l’accident en bicicleta d’un infant que cau, es fa mal, sagna i el seu pare el cura. A partir d’aquí, hem entrevistat 135 infants de P3, P4 i P5, mitjançant els 3 models d’entrevista referits, enfrontant-los a una demanda específica: recordar i narrar aquest esdeveniment. S’ha conclòs que el nivell de record correcte, quan s’utilitza un model d’entrevista adequat amb els infants en edat preescolar, oscil•la entre el 70-90%, fet que permet defensar la confiança en els records dels infants. Es constata que el percentatge d’emissions incorrectes dels infants en edat preescolar és mínim, al voltant d’un 5-6%. L’estudi remarca la necessitat d’establir perfectament les regles de l’entrevista i, per últim, en destaca la ineficàcia de les tècniques de memòria de l’entrevista cognitiva en els infants de P3 i P4. En els de P5 es comencen a veure beneficis gràcies a la tècnica de la reinstauració contextual (RC), estant les altres tècniques fora de la comprensió i utilització dels infants d’aquestes edats. Interviewing preschoolers victims of sexual abuse and/or domestic abuse: Effectiveness of forensic interviews models 135 preschool children were interviewed with 3 different interview models in order to remember a significant emotional event. Authors conclude that the correct recall of children ranging from 70-90% and the percentage of error messages is 5-6%. It is necessary to fully establish the rules of the interview. The present research highlights the effectiveness of the cognitive interview techniques in children from P3 and P4. Entrevistando niños preescolares víctimas de abuso sexual y/o maltrato familiar: eficacia de los modelos de entrevista forense Se han entrevistado 135 niños preescolares con 3 modelos de entrevista diferentes para recordar un hecho emocionalmente significativo. Se concluye que el recuerdo correcto de los niños oscila entre el 70-90% y el porcentaje de errores de mensajes es del 5-6%. El estudio remarca la necesidad de establecer perfectamente las reglas de la entrevista y se destaca la ineficacia de las técnicas de la entrevista cognitiva en los niños de P3 y P4.

Three-dimensional models of 14α-sterol demethylase (Cyp51A) from Aspergillus lentulus and Aspergillus fumigatus: an insight into differences in voriconazole interaction.

Aspergillus lentulus, an Aspergillus fumigatus sibling species, is increasingly reported in corticosteroid-treated patients. Its clinical significance is unknown, but the fact that A. lentulus shows reduced antifungal susceptibility, mainly to voriconazole, is of serious concern. Heterologous expression of cyp51A from A. fumigatus and A. lentulus was performed in Saccharomyces cerevisiae to assess differences in the interaction of Cyp51A with the azole drugs. The absence of endogenous ERG11 was efficiently complemented in S. cerevisiae by the expression of either Aspergillus cyp51A allele. There was a marked difference between azole minimum inhibitory concentration (MIC) values of the clones expressing each Aspergillus spp. cyp51A. Saccharomyces cerevisiae clones expressing A. lentulus alleles showed higher MICs to all of the azoles tested, supporting the hypothesis that the intrinsic azole resistance of A. lentulus could be associated with Cyp51A. Homology models of A. fumigatus and A. lentulus Cyp51A protein based on the crystal structure of Cyp51p from Mycobacterium tuberculosis in complex with fluconazole were almost identical owing to their mutual high sequence identity. Molecular dynamics (MD) was applied to both three-dimensional protein models to refine the homology modelling and to explore possible differences in the Cyp51A-voriconazole interaction. After 20ns of MD modelling, some critical differences were observed in the putative closed form adopted by the protein upon voriconazole binding. A closer study of the A. fumigatus and A. lentulus voriconazole putative binding site in Cyp51A suggested that some major differences in the protein's BC loop could differentially affect the lock-up of voriconazole, which in turn could correlate with their different azole susceptibility profiles.

Predictive models of syncope causes in an outpatient clinic

The investigation of unexplained syncope remains a challenging clinical problem. In the present study we sought to evaluate the diagnostic value of a standardized work-up focusing on non invasive tests in patients with unexplained syncope referred to a syncope clinic, and whether certain combinations of clinical parameters are characteristic of rhythmic and reflex causes of syncope. METHODS AND RESULTS: 317 consecutive patients underwent a standardized work-up including a 12-lead ECG, physical examination, detailed history with screening for syncope-related symptoms using a structured questionnaire followed by carotid sinus massage (CSM), and head-up tilt test. Invasive testings including an electrophysiological study and implantation of a loop recorder were only performed in those with structural heart disease or traumatic syncope. Our work-up identified an etiology in 81% of the patients. Importantly, three quarters of the causes were established non invasively combining head-up tilt test, CSM and hyperventilation testing. Invasive tests yielded an additional 7% of diagnoses. Logistic analysis identified age and number of significant prodromes as the only predictive factors of rhythmic syncope. The same two factors, in addition to the duration of the ECG P-wave, were also predictive of vasovagal and psychogenic syncope. These factors, optimally combined in predictive models, showed a high negative and a modest positive predictive value. CONCLUSION: A standardized work-up focusing on non invasive tests allows to establish more than three quarters of syncope causes. Predictive models based on simple clinical parameters may help to distinguish between rhythmic and other causes of syncope

Ambulatory healthcare information system: a conceptual framework

Despite the tremendous amount of data collected in the field of ambulatory care, political authorities still lack synthetic indicators to provide them with a global view of health services utilization and costs related to various types of diseases. Moreover, public health indicators fail to provide useful information for physicians' accountability purposes. The approach is based on the Swiss context, which is characterized by the greatest frequency of medical visits in Europe, the highest rate of growth for care expenditure, poor public information but a lot of structured data (new fee system introduced in 2004). The proposed conceptual framework is universal and based on descriptors of six entities: general population, people with poor health, patients, services, resources and effects. We show that most conceptual shortcomings can be overcome and that the proposed indicators can be achieved without threatening privacy protection, using modern cryptographic techniques. Twelve indicators are suggested for the surveillance of the ambulatory care system, almost all based on routinely available data: morbidity, accessibility, relevancy, adequacy, productivity, efficacy (from the points of view of the population, people with poor health, and patients), effectiveness, efficiency, health services coverage and financing. The additional costs of this surveillance system should not exceed Euro 2 million per year (Euro 0.3 per capita).

Multi-stage oligopoly models with nested logit demand structures: A simplifying approach

Solving multi-stage oligopoly models by backward induction can easily become a com- plex task when rms are multi-product and demands are derived from a nested logit frame- work. This paper shows that under the assumption that within-segment rm shares are equal across segments, the analytical expression for equilibrium pro ts can be substantially simpli ed. The size of the error arising when this condition does not hold perfectly is also computed. Through numerical examples, it is shown that the error is rather small in general. Therefore, using this assumption allows to gain analytical tractability in a class of models that has been used to approach relevant policy questions, such as for example rm entry in an industry or the relation between competition and location. The simplifying approach proposed in this paper is aimed at helping improving these type of models for reaching more accurate recommendations.