KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging

Several strategies relying on kriging have recently been proposed for adaptively estimating contour lines and excursion sets of functions under severely limited evaluation budget. The recently released R package KrigInv 3 is presented and offers a sound implementation of various sampling criteria for those kinds of inverse problems. KrigInv is based on the DiceKriging package, and thus benefits from a number of options concerning the underlying kriging models. Six implemented sampling criteria are detailed in a tutorial and illustrated with graphical examples. Different functionalities of KrigInv are gradually explained. Additionally, two recently proposed criteria for batch-sequential inversion are presented, enabling advanced users to distribute function evaluations in parallel on clusters or clouds of machines. Finally, auxiliary problems are discussed. These include the fine tuning of numerical integration and optimization procedures used within the computation and the optimization of the considered criteria.

Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package

Kriging-based optimization relying on noisy evaluations of complex systems has recently motivated contributions from various research communities. Five strategies have been implemented in the DiceOptim package. The corresponding functions constitute a user-friendly tool for solving expensive noisy optimization problems in a sequential framework, while offering some flexibility for advanced users. Besides, the implementation is done in a unified environment, making this package a useful device for studying the relative performances of existing approaches depending on the experimental setup. An overview of the package structure and interface is provided, as well as a description of the strategies and some insight about the implementation challenges and the proposed solutions. The strategies are compared to some existing optimization packages on analytical test functions and show promising performances.

Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.

Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

Stepwise uncertainty reduction (SUR) strategies aim at constructing a sequence of points for evaluating a function  f in such a way that the residual uncertainty about a quantity of interest progressively decreases to zero. Using such strategies in the framework of Gaussian process modeling has been shown to be efficient for estimating the volume of excursion of f above a fixed threshold. However, SUR strategies remain cumbersome to use in practice because of their high computational complexity, and the fact that they deliver a single point at each iteration. In this article we introduce several multipoint sampling criteria, allowing the selection of batches of points at which f can be evaluated in parallel. Such criteria are of particular interest when f is costly to evaluate and several CPUs are simultaneously available. We also manage to drastically reduce the computational cost of these strategies through the use of closed form formulas. We illustrate their performances in various numerical experiments, including a nuclear safety test case. Basic notions about kriging, auxiliary problems, complexity calculations, R code, and data are available online as supplementary materials.

Multifractional Poisson process, multistable subordinator and related limit theorems

We introduce a multistable subordinator, which generalizes the stable subordinator to the case of time-varying stability index. This enables us to define a multifractional Poisson process. We study properties of these processes and establish the convergence of a continuous-time random walk to the multifractional Poisson process.

Saddlepoint Approximations to the Probability of Ruin in Finite Time for the Compound Poisson Risk Process Perturbed by Diffusion

A large deviations type approximation to the probability of ruin within a finite time for the compound Poisson risk process perturbed by diffusion is derived. This approximation is based on the saddlepoint method and generalizes the approximation for the non-perturbed risk process by Barndorff-Nielsen and Schmidli (Scand Actuar J 1995(2):169–186, 1995). An importance sampling approximation to this probability of ruin is also provided. Numerical illustrations assess the accuracy of the saddlepoint approximation using importance sampling as a benchmark. The relative deviations between saddlepoint approximation and importance sampling are very small, even for extremely small probabilities of ruin. The saddlepoint approximation is however substantially faster to compute.

The Discontinuous Nature of Kriging Interpolation for Digital Terrain Modeling

Kriging is a widely employed method for interpolating and estimating elevations from digital elevation data. Its place of prominence is due to its elegant theoretical foundation and its convenient practical implementation. From an interpolation point of view, kriging is equivalent to a thin-plate spline and is one species among the many in the genus of weighted inverse distance methods, albeit with attractive properties. However, from a statistical point of view, kriging is a best linear unbiased estimator and, consequently, has a place of distinction among all spatial estimators because any other linear estimator that performs as well as kriging (in the least squares sense) must be equivalent to kriging, assuming that the parameters of the semivariogram are known. Therefore, kriging is often held to be the gold standard of digital terrain model elevation estimation. However, I prove that, when used with local support, kriging creates discontinuous digital terrain models, which is to say, surfaces with “rips” and “tears” throughout them. This result is general; it is true for ordinary kriging, kriging with a trend, and other forms. A U.S. Geological Survey (USGS) digital elevation model was analyzed to characterize the distribution of the discontinuities. I show that the magnitude of the discontinuity does not depend on surface gradient but is strongly dependent on the size of the kriging neighborhood.

Hazardous air pollutants and childhood lymphohematopoietic cancer in Southeast Texas, 1995--2004

Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

Una aplicación del proceso de Poisson en la enseñanza y aprendizaje de la estadística

En los últimos años se ha dado un incremento en la preocupación social por los problemas relacionados con la calidad de los servicios, y en particular, de la enseñanza universitaria. El objetivo de este trabajo es presentar una propuesta que sirva de orientación en el aprendizaje de algunas técnicas y metodologías estadísticas adecuadas para el alumno de grado en distintas carreras universitarias. Se pretende lograr una mejor enseñanza de la asignatura Estadística basándose en la resolución de problemas y de casos prácticos con datos reales de diversos aspectos del ámbito de la tecnología y de las ciencias. Para lograr con los objetivos planteados se presenta, a modo de ejemplo, una aplicación al estudio del proceso de Poisson. En particular se realiza un estudio estadístico del tráfico de automóviles particulares que pasan por un punto fijo de la autopista La Plata-Buenos Aires.

Una aplicación del proceso de Poisson en la enseñanza y aprendizaje de la estadística

En los últimos años se ha dado un incremento en la preocupación social por los problemas relacionados con la calidad de los servicios, y en particular, de la enseñanza universitaria. El objetivo de este trabajo es presentar una propuesta que sirva de orientación en el aprendizaje de algunas técnicas y metodologías estadísticas adecuadas para el alumno de grado en distintas carreras universitarias. Se pretende lograr una mejor enseñanza de la asignatura Estadística basándose en la resolución de problemas y de casos prácticos con datos reales de diversos aspectos del ámbito de la tecnología y de las ciencias. Para lograr con los objetivos planteados se presenta, a modo de ejemplo, una aplicación al estudio del proceso de Poisson. En particular se realiza un estudio estadístico del tráfico de automóviles particulares que pasan por un punto fijo de la autopista La Plata-Buenos Aires.

Análisis de la distribución espacial de centros eruptivos monogenéticos en las Islas Canarias según el análisis de vecino más próximo de Poisson.

El objetivo principal de este trabajo es estudiar la distribución espacial de los centros eruptivos monogenéticos según el análisis de vecino más próximo de Poisson, propuesto por Clark y Evans (1954), en las Islas Canarias. Se pretende adquirir así unos valores cuantitativos que permitan interpretar si los centros eruptivos monogenéticos se distribuyen de forma aleatoria, concentrada o dispersa en cada isla. La confrontación de estos resultados con la bibliografía ayudará a interpretarlos mediante comparación. Como objetivo secundario y parte fundamental del trabajo se presenta la necesidad y el fin de adquirir conocimientos teóricos y prácticos de análisis espacial, además de destreza en el uso de lenguajes y entornos de programación adecuados para este tipo de estudios. Otro de los objetivos es desarrollar una aplicación que haga extensible este tipo de estudios de forma sencilla y ponga a disposición, en el caso de una publicación final, de la comunidad científica y de los usuarios a nivel universitario, una herramienta eficaz de análisis cuantitativo para hallar los índices requeridos para llevar a cabo el análisis de vecino más próximo de Poisson. El área de estudio son las Islas Canarias que conforman un archipiélago de siete islas mayores (Fig. 1): Tenerife, Fuerteventura, Gran Canaria, Lanzarote, La Palma, La Gomera y El Hierro; cuatro islas menores: Lobos, La Graciosa, Montaña Clara y Alegranza; y varios roques. Queda comprendido entre los paralelos 27 º 37 ' N y 29 º 35 ' N (Punta de La Restinga, en El Hierro; Punta de los Mosegos, en la isla de la Alegranza) y entre los meridianos 13 º 20 ' W y 18 º 10 ' W (Roque del Este; Punta de Orchilla, en El Hierro) y se encuentra a distancias de entre 100 km y 500 km de la costa noroccidental africana. Queda englobado dentro de la región de la Macaronesia, conjunto de cinco archipiélagos de origen volcánico situado en el Atlántico Oriental, a saber: Azores, Madeira, Salvajes, Canarias y Cabo Verde; y está limitada por los paralelos 14 º 49 ' N y 39 º 45 ' N, y por los meridianos 13 º 20 ' W y 31 º 17 ' W, estando separados entre sus puntos norte y sur por 2 700 km y entre sus puntos este y oeste por 1 800 km de distancia (Gosálvez et al., 2010). Sobre el origen del archipiélago y su contexto geodinámico, se han propuesto varias hipótesis, e.g.: Carracedo et al. (1998), Anguita y Hernán (2000), Ancochea et al. (2006), en las que aún no queda completamente claro el origen de la Islas Canarias, ya que algunos dan un protagonismo mayor a la actividad tectónica como causante del ascenso del magma a través de la corteza y otros defienden la existencia de un punto caliente como verdadera causa del volcanismo en Canarias.