Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Generalized Langevin equations: Anomalous diffusion and probability distributions

We study the motion of a particle governed by a generalized Langevin equation. We show that, when no fluctuation-dissipation relation holds, the long-time behavior of the particle may be from stationary to superdiffusive, along with subdiffusive and diffusive. When the random force is Gaussian, we derive the exact equations for the joint and marginal probability density functions for the position and velocity of the particle and find their solutions.

Time of ruin in a risk model with generalized Erlang (n) interclaim times and a constant dividend barrier

In this paper we analyze the time of ruin in a risk process with the interclaim times being Erlang(n) distributed and a constant dividend barrier. We obtain an integro-differential equation for the Laplace Transform of the time of ruin. Explicit solutions for the moments of the time of ruin are presented when the individual claim amounts have a distribution with rational Laplace transform. Finally, some numerical results and a compare son with the classical risk model, with interclaim times following an exponential distribution, are given.

Letter to the Editor : on the value of probability for evaluating results of comparative pattern analyses

This letter to the Editor comments on the article Practical relevance of pattern uniqueness in forensic science by P.T. Jayaprakash (Forensic Science International, in press).

Variation in forest fire ignition probability in Finland

Abstract

Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation

Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Comparisons of Estimates of Annual Exceedance-Probability Discharges for Small Drainage Basins in Iowa, Based on Data through Water Year 2013, TR-678, 2015

Traditionally, the Iowa Department of Transportation has used the Iowa Runoff Chart and single-variable regional-regression equations (RREs) from a U.S. Geological Survey report (published in 1987) as the primary methods to estimate annual exceedance-probability discharge (AEPD) for small (20 square miles or less) drainage basins in Iowa. With the publication of new multi- and single-variable RREs by the U.S. Geological Survey (published in 2013), the Iowa Department of Transportation needs to determine which methods of AEPD estimation provide the best accuracy and the least bias for small drainage basins in Iowa. Twenty five streamgages with drainage areas less than 2 square miles (mi2) and 55 streamgages with drainage areas between 2 and 20 mi2 were selected for the comparisons that used two evaluation metrics. Estimates of AEPDs calculated for the streamgages using the expected moments algorithm/multiple Grubbs-Beck test analysis method were compared to estimates of AEPDs calculated from the 2013 multivariable RREs; the 2013 single-variable RREs; the 1987 single-variable RREs; the TR-55 rainfall-runoff model; and the Iowa Runoff Chart. For the 25 streamgages with drainage areas less than 2 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the TR-55 method for flood regions 1 and 3 (published in 2013) and by using the 1987 single-variable RREs for flood region 2 (published in 2013). For drainage basins with areas between 2 and 20 mi2, results of the comparisons seem to indicate the best overall accuracy and the least bias may be achieved by using the 1987 single-variable RREs for the Southern Iowa Drift Plain landform region and for flood region 3 (published in 2013), by using the 2013 multivariable RREs for the Iowan Surface landform region, and by using the 2013 or 1987 single-variable RREs for flood region 2 (published in 2013). For all other landform or flood regions in Iowa, use of the 2013 single-variable RREs may provide the best overall accuracy and the least bias. An examination was conducted to understand why the 1987 single-variable RREs seem to provide better accuracy and less bias than either of the 2013 multi- or single-variable RREs. A comparison of 1-percent annual exceedance-probability regression lines for hydrologic regions 1–4 from the 1987 single-variable RREs and for flood regions 1–3 from the 2013 single-variable RREs indicates that the 1987 single-variable regional-regression lines generally have steeper slopes and lower discharges when compared to 2013 single-variable regional-regression lines for corresponding areas of Iowa. The combination of the definition of hydrologic regions, the lower discharges, and the steeper slopes of regression lines associated with the 1987 single-variable RREs seem to provide better accuracy and less bias when compared to the 2013 multi- or single-variable RREs; better accuracy and less bias was determined particularly for drainage areas less than 2 mi2, and also for some drainage areas between 2 and 20 mi2. The 2013 multi- and single-variable RREs are considered to provide better accuracy and less bias for larger drainage areas. Results of this study indicate that additional research is needed to address the curvilinear relation between drainage area and AEPDs for areas of Iowa.

On optimal dividend strategies with deficit or incomplete information

Rapport de synthèse Cette thèse consiste en trois essais sur les stratégies optimales de dividendes. Chaque essai correspond à un chapitre. Les deux premiers essais ont été écrits en collaboration avec les Professeurs Hans Ulrich Gerber et Elias S. W. Shiu et ils ont été publiés; voir Gerber et al. (2006b) ainsi que Gerber et al. (2008). Le troisième essai a été écrit en collaboration avec le Professeur Hans Ulrich Gerber. Le problème des stratégies optimales de dividendes remonte à de Finetti (1957). Il se pose comme suit: considérant le surplus d'une société, déterminer la stratégie optimale de distribution des dividendes. Le critère utilisé consiste à maximiser la somme des dividendes escomptés versés aux actionnaires jusqu'à la ruine2 de la société. Depuis de Finetti (1957), le problème a pris plusieurs formes et a été résolu pour différents modèles. Dans le modèle classique de théorie de la ruine, le problème a été résolu par Gerber (1969) et plus récemment, en utilisant une autre approche, par Azcue and Muler (2005) ou Schmidli (2008). Dans le modèle classique, il y a un flux continu et constant d'entrées d'argent. Quant aux sorties d'argent, elles sont aléatoires. Elles suivent un processus à sauts, à savoir un processus de Poisson composé. Un exemple qui correspond bien à un tel modèle est la valeur du surplus d'une compagnie d'assurance pour lequel les entrées et les sorties sont respectivement les primes et les sinistres. Le premier graphique de la Figure 1 en illustre un exemple. Dans cette thèse, seules les stratégies de barrière sont considérées, c'est-à-dire quand le surplus dépasse le niveau b de la barrière, l'excédent est distribué aux actionnaires comme dividendes. Le deuxième graphique de la Figure 1 montre le même exemple du surplus quand une barrière de niveau b est introduite, et le troisième graphique de cette figure montre, quand à lui, les dividendes cumulés. Chapitre l: "Maximizing dividends without bankruptcy" Dans ce premier essai, les barrières optimales sont calculées pour différentes distributions du montant des sinistres selon deux critères: I) La barrière optimale est calculée en utilisant le critère usuel qui consiste à maximiser l'espérance des dividendes escomptés jusqu'à la ruine. II) La barrière optimale est calculée en utilisant le second critère qui consiste, quant à lui, à maximiser l'espérance de la différence entre les dividendes escomptés jusqu'à la ruine et le déficit au moment de la ruine. Cet essai est inspiré par Dickson and Waters (2004), dont l'idée est de faire supporter aux actionnaires le déficit au moment de la ruine. Ceci est d'autant plus vrai dans le cas d'une compagnie d'assurance dont la ruine doit être évitée. Dans l'exemple de la Figure 1, le déficit au moment de la ruine est noté R. Des exemples numériques nous permettent de comparer le niveau des barrières optimales dans les situations I et II. Cette idée, d'ajouter une pénalité au moment de la ruine, a été généralisée dans Gerber et al. (2006a). Chapitre 2: "Methods for estimating the optimal dividend barrier and the probability of ruin" Dans ce second essai, du fait qu'en pratique on n'a jamais toute l'information nécessaire sur la distribution du montant des sinistres, on suppose que seuls les premiers moments de cette fonction sont connus. Cet essai développe et examine des méthodes qui permettent d'approximer, dans cette situation, le niveau de la barrière optimale, selon le critère usuel (cas I ci-dessus). Les approximations "de Vylder" et "diffusion" sont expliquées et examinées: Certaines de ces approximations utilisent deux, trois ou quatre des premiers moments. Des exemples numériques nous permettent de comparer les approximations du niveau de la barrière optimale, non seulement avec les valeurs exactes mais également entre elles. Chapitre 3: "Optimal dividends with incomplete information" Dans ce troisième et dernier essai, on s'intéresse à nouveau aux méthodes d'approximation du niveau de la barrière optimale quand seuls les premiers moments de la distribution du montant des sauts sont connus. Cette fois, on considère le modèle dual. Comme pour le modèle classique, dans un sens il y a un flux continu et dans l'autre un processus à sauts. A l'inverse du modèle classique, les gains suivent un processus de Poisson composé et les pertes sont constantes et continues; voir la Figure 2. Un tel modèle conviendrait pour une caisse de pension ou une société qui se spécialise dans les découvertes ou inventions. Ainsi, tant les approximations "de Vylder" et "diffusion" que les nouvelles approximations "gamma" et "gamma process" sont expliquées et analysées. Ces nouvelles approximations semblent donner de meilleurs résultats dans certains cas.

Defining risk thresholds for a 10-year probability of hip fracture model that combines clinical risk factors and quantitative ultrasound: results using the EPISEM cohort.

Using a large prospective cohort of over 12,000 women, we determined 2 thresholds (high risk and low risk of hip fracture) to use in a 10-yr hip fracture probability model that we had previously described, a model combining the heel stiffness index measured by quantitative ultrasound (QUS) and a set of easily determined clinical risk factors (CRFs). The model identified a higher percentage of women with fractures as high risk than a previously reported risk score that combined QUS and CRF. In addition, it categorized women in a way that was quite consistent with the categorization that occurred using dual X-ray absorptiometry (DXA) and the World Health Organization (WHO) classification system; the 2 methods identified similar percentages of women with and without fractures in each of their 3 categories, but the 2 identified only in part the same women. Nevertheless, combining our composite probability model with DXA in a case findings strategy will likely further improve the detection of women at high risk of fragility hip fracture. We conclude that the currently proposed model may be of some use as an alternative to the WHO classification criteria for osteoporosis, at least when access to DXA is limited.