Modelling air pollution data by the skew-normal distribution

Particulate matter with an aerodynamic equivalent diameter of up 10 μm is commonly referred to as PM₁₀ and its harmful effects on human health are well known. We model annual means of daily concentrations of PM₁₀ in Italy by the skew-normal distribution, giving theoretical as well as empirical motivations for the model’s choice. Its adequacy is checked through Anderson–Darling statistic. The skew-normal distribution gives a very good fit to the data and it is particularly useful in estimating probabilities of high PM₁₀ concentrations.     

A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro,Italy)

Habitat Suitability (HS) models have been extensively used by conservation planners to estimate the spatial distribution of threatened species and of species of commercial interest. In this work we compare three HS models for the estimation of commercial yield potential and the identification of suitable sites for Tapes philippinarum rearing in the Sacca di Goro lagoon (Italy) on the basis of six environmental factors. The habitat suitability index (HSI) is based on expert opinion while the habitat suitability conditional (HSC) is calibrated on observational data. The habitat suitability mixed (HSM) model is a two-part model combining expert knowledge and regression analysis: the first component of the model uses logistic regression to identify the areas in which clams are likely to be present; the second part applies the same parameter-specific suitability functions of the HSI model only in the areas previously identified as productive by the logistic component.The HS models were validated on an independent data set and estimates of potential yield of the Goro lagoon were compared. The effectiveness of the three approaches is then discussed in terms of predicted yield and identification of suitable sites for farming.     

Compositional variation in three Cascade stratovolcanoes: Jefferson,Rainier, and Shasta

Detailed major and trace element studies of volcanic rocks from Jefferson, Rainier, and Shasta stratovolcanoes in the Cascade Range indicate that each volcano has distinct geochemical distribution patterns. Silica variation diagrams are not smooth nor, in general, continuous for any volcano. Portions of stratigraphic sections within the volcanoes exhibit compositional coherency and are interpreted as eruptive groups which were extruded over time intervals which are short compared to the lifetimes of the volcanoes. The results of this investigation indicate the leasibility of geochemically mapping eruptive groups within stratovolcanoes. Systematic compositional trends are not observed within thick (500–1000 m) eruptive groups but may occur over thicknesses of <200 m. Compositional variations within eruptive groups are commonly non-systematic and show ranges similar to the ranges observed in individual flows. Correlations between the amounts or kinds of phenocryst phases present and intra-group compositional variation is not observed. Inter-group compositional differences are sometimes accompanied by mineralogical differences. Late andesites and dacites at Rainier and Shasta are characterized by decreases in K and Rb while at Jefferson increases in these elements and other compositional changes occur in the late eruptives. Progressive fractional crystallization models do not seem capable of explaining the element distributions observed in the three volcanoes. Existing data are consistent with a model involving varying degrees of melting of some combination of amphibolite, eclogite or peridotite in or above a subduction zone with varying water contents. Segregation and sequential eruption of small batches of magma may produce the eruptive groups characterizing the volcanoes. Late mafic magmas erupted at satellite vents appear to be produced in different (deeper?) mantle source areas.     

A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro, Italy)

Habitat Suitability (HS) models have been extensively used by conservation planners to estimate the spatial distribution of threatened species and of species of commercial interest. In this work we compare three HS models for the estimation of commercial yield potential and the identification of suitable sites for Tapes philippinarum rearing in the Sacca di Goro lagoon (Italy) on the basis of six environmental factors. The habitat suitability index (HSI) is based on expert opinion while the habitat suitability conditional (HSC) is calibrated on observational data. The habitat suitability mixed (HSM) model is a two-part model combining expert knowledge and regression analysis: the first component of the model uses logistic regression to identify the areas in which clams are likely to be present; the second part applies the same parameter-specific suitability functions of the HSI model only in the areas previously identified as productive by the logistic component.The HS models were validated on an independent data set and estimates of potential yield of the Goro lagoon were compared. The effectiveness of the three approaches is then discussed in terms of predicted yield and identification of suitable sites for farming.     

A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro, Italy)

Habitat Suitability (HS) models have been extensively used by conservation planners to estimate the spatial distribution of threatened species and of species of commercial interest. In this work we compare three HS models for the estimation of commercial yield potential and the identification of suitable sites for Tapes philippinarum rearing in the Sacca di Goro lagoon (Italy) on the basis of six environmental factors. The habitat suitability index (HSI) is based on expert opinion while the habitat suitability conditional (HSC) is calibrated on observational data. The habitat suitability mixed (HSM) model is a two-part model combining expert knowledge and regression analysis: the first component of the model uses logistic regression to identify the areas in which clams are likely to be present; the second part applies the same parameter-specific suitability functions of the HSI model only in the areas previously identified as productive by the logistic component. The HS models were validated on an independent data set and estimates of potential yield of the Goro lagoon were compared. The effectiveness of the three approaches is then discussed in terms of predicted yield and identification of suitable sites for farming.     

以空间光滑的地震活动性模型为空间分布函数的地震危险性分析方法

根据华北地区的地震目录,建立了4个空间光滑的地震活动性模型,并以这些模型为空间分布函数,将华北地震区每个地震带的地震年发生率分配到空间格点中,计算这一地区的地震危险性．结果表明,采用仪器记录地震计算得到的地震活动性模型和地震危险性结果能够反映华北地区现今的地震活动水平和地震危险性水平,符合人们对现今华北地区地震危险性的认识;采用历史破坏性地震（Mge;4.7）计算的地震活动性模型和地震危险性结果,较好地反映了华北地区中强地震活动区的地震危险性水平;以地震应变计算地震活动率,并根据点椭圆模型和线椭圆模型计算得到的地震活动性模型,能够较好地反映大地震的活动水平和空间构造特征．将根据4个模型计算得到的50年超越概率10%峰值加速度（PGA）分布加权平均,得到综合的华北地区PGA分布,并将该PGA分布与根据《中国地震动参数区划图》中综合潜源方案计算得到的50年超越概率10%的PGA分布做了比较,发现二者无本质差别,均能反映华北地震区的地震危险性水平．当然,二者也具有一定的差异:前者计算得到的符合PGAge;100 cm/s2条件的区域面积明显要比后者的大,而符合PGAge;250 cm/s2条件的区域面积则比后者的要小. 这主要是由于潜在震源区类型和空间分布函数不同造成的．      

Trivariate generalized extreme value distribution in flood frequency analysis

Abstract

The multivariate extension of the logistic model with generalized extreme value (GEV) marginals is applied to provide a regional at-site flood estimate. The maximum likelihood estimators of the parameters were obtained numerically by using a multivariable constrained optimization algorithm. The asymptotic results were checked by distribution sampling techniques in order to establish whether or not those results can be utilized for small samples. A region in northern Mexico with 21 gauging stations was selected to apply the model. Results were compared with those obtained by the most popular univariate distributions, the bivariate approach of the logistic model and three regional methods: station-year, index flood and L-moments. These show that there is a reduction in the standard error of fit when estimating the parameters of the marginal distribution with the trivariate distribution instead of its univariate and bivariate counterpart, and differences between at-site and regional at-site design events can be significant as return period increases.     

Study of the Non-Uniform Distribution of Earthquake Risk Within Potential Sources

Potential sources are aggregates of probable future epicenters.In this area,for source models currently,in common use for seismic risk analysis in China,the mean area of each potential source is about 3000-4000 km2.It is assumed that seismic risk has a uniform distribution within the range of each potential source,but studies have shown that the uniform distribution model to a large extent may give an underestimation of the seismic risk.In this paper,the relative distribution of historical epicenters in space within potential sources is discussed,a method is proposed to quantitatively describe the non-uniform distribution of strong earthquakes within potential sources,and some preliminary results are given.By using the results of this paper,seismic risk analysis and seismic zonation can be made more scientific and more reasonable.     

Models for extremes using the extended three-parameter Burr XII system with application to flood frequency analysis / Modèles d’extrêmes utilisant le système Burr XII étendu à trois paramètres et application à l’analyse fréquentielle des crues

Abstract

Abstract A new theoretically-based distribution in frequency analysis is proposed. The extended three-parameter Burr XII distribution includes the generalized Pareto distribution, which is used to model the exceedences over threshold; log-logistic distribution, which is also advocated in flood frequency analysis; and Weibull distribution, which is a part of the generalized extreme value distribution used to model annual maxima as special cases. The extended Burr distribution is flexible to approximate extreme value distribution. Note that both the generalized Pareto and generalized extreme value distributions are limiting results in modelling the exceedences over threshold and block extremes, respectively. From a modelling perspective, generalization might be necessary in order to obtain a better fit. The extended three-parameter Burr XII distribution is therefore a meaningful candidate distribution in the frequency analysis. Maximum likelihood estimation for this distribution is investigated in the paper. The use of the extended three-parameter Burr XII distribution is demonstrated using data from China.     

Apparent/spurious multifractality of data sampled from fractional Brownian/Lévy motions

Many earth and environmental variables appear to be self‐affine (monofractal) or multifractal with spatial (or temporal) increments having exceedance probability tails that decay as powers of − α where 1 < α ≤ 2. The literature considers self‐affine and multifractal modes of scaling to be fundamentally different, the first arising from additive and the second from multiplicative random fields or processes. We demonstrate theoretically that data having finite support, sampled across a finite domain from one or several realizations of an additive Gaussian field constituting fractional Brownian motion (fBm) characterized by α = 2, give rise to positive square (or absolute) increments which behave as if the field was multifractal when in fact it is monofractal. Sampling such data from additive fractional Lévy motions (fLm) with 1 < α < 2 causes them to exhibit spurious multifractality. Deviations from apparent multifractal behaviour at small and large lags are due to nonzero data support and finite domain size, unrelated to noise or undersampling (the causes cited for such deviations in the literature). Our analysis is based on a formal decomposition of anisotropic fLm (fBm when α = 2) into a continuous hierarchy of statistically independent and homogeneous random fields, or modes, which captures the above behaviour in terms of only E + 3 parameters where E is Euclidean dimension. Although the decomposition is consistent with a hydrologic rationale proposed by Neuman (2003), its mathematical validity is independent of such a rationale. Our results suggest that it may be worth checking how closely would variables considered in the literature to be multifractal (e.g. experimental and simulated turbulent velocities, some simulated porous flow velocities, landscape elevations, rain intensities, river network area and width functions, river flow series, soil water storage and physical properties) fit the simpler monofractal model considered in this paper (such an effort would require paying close attention to the support and sampling window scales of the data). Parsimony would suggest associating variables found to fit both models equally well with the latter. Copyright © 2010 John Wiley & Sons, Ltd.     

A framework to estimate sediment loads using distributions with covariates: Beaurivage River watershed (Québec,Canada)

A framework to estimate sediment loads based on the statistical distribution of sediment concentrations and various functional forms relating distribution characteristics (e.g. mean and variance) to covariates is developed. The covariates are used as surrogates to represent the main processes involved in sediment generation and transport. Statistical models of increasing complexity are built and compared to assess their relative performance using available sediment concentration and covariate data. Application to the Beaurivage River watershed (Québec, Canada) is conducted using data for the 1989–2004 period. The covariates considered in this application are streamflow and calendar day. A comparison of different statistical models shows that, in this case, the log‐normal distribution with a mean value depending on streamflow (power law with an additive term) and calendar day (sinusoidal), a constant coefficient of variation for streamflow dependence and a constant standard deviation for calendar day dependence provide the best result. Model parameters are estimated using the maximum likelihood estimation technique. The selected model is then used to estimate the distribution of annual sediment loads for the Beaurivage River watershed for a selected period. A bootstrap parametric method is implemented to account for uncertainties in parameter values and to build the distributions of annual loads. Comparison of model results with estimates obtained using the empirical ratio estimator shows that the latter were rarely within the 0·1–0·9 quantile interval of the distributions obtained with the proposed approach. Copyright © 2008 John Wiley & Sons, Ltd.     

基于卡方分布函数的辐射带电子蝴蝶状投掷角分布的优化判别方法

受不同物理过程影响,辐射带电子呈现多种投掷角分布类型,其中蝴蝶状分布尤为引人关注,其特征为通量在90°投掷角附近有极小值、在较低投掷角处达到峰值.现有研究普遍通过对几个特定投掷角间的通量比值进行限定来识别蝴蝶状分布,然而,该方法所挑选的电子分布并不一定符合蝴蝶状分布特征,这为准确研究电子蝴蝶状分布的现象学规律及其背后物...     

Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model： a case study of the Sabae Area, Japan

A number of statistical methods are typically used to effectively predict potential landslide distributions. In this study two multivariate statistical analysis methods were used （weights of evidence and logistic regression） to predict the potential distribution of shallow-seated landslides in the Kamikawachi area of Sabae City, Fukui Prefecture, Japan. First, the dependent variable （shallow-seated landslides） was divided into presence and absence, and the independent variables （environmental factors such as slope and altitude） were categorized according to their characteristics. Then, using the weights of evidence （WE） method, the weights of pairs comprising presence （w^＋（i）） or absence （w^-（i））, and the contrast values for each category of independent variable （evidence）, were calculated, Using the method that integrated the weights of evidence method and a logistic regression model, score values were calculated for each category of independent variable. Based on these contrast values, three models were selected to sum the score values of every gird in the study area. According to a receiver operating characteristic curve analysis （ROC）, model 2 yielded the best fit for predicting the potential distribution of shallow-seated landslide hazards, with 89% correctness and a 54.5% hit ratio when the occurrence probability （OP） of landslides was 70%. The model was tested using data from an area close to the study region, and showed 94% correctness and a hit ratio of 45.7% when the OP of landslides was 70%. Finally, the potential distribution of shallow-seated landslides, based on the OP, was mapped using a geographical information system.     

Discussion on the Relation Between the Probabilistic Distribution of Magnitude in a Seismic Province and That in an Area with Potential Seismic Source

According to the joint probabilistic distribution model of magnitude and space,the author discusses the relationship between the probabilistic distribution of magnitude in a seismic province and that in an area with potential seismic sources.The results show that if the magnitude probabilistic distribution follows the truncated exponential form in a seismic province,there must be some potential source in which the magnitude probabilistic distribution does not conform to that form.The result is consistent with the concept of "characteristic earthquake" derived from the study of actual records of seismicity and the study of geology.The author suggests that the relationship between the probabilistic distribution of magnitude in a seismic province and that in a seismic potential area must be considered in the study of the analysis of seismicity,seismic zonation and engineering seismology,for the purpose of the evaluation of the probabilistic distribution of magnitude correctly in every area with potential s     

基于ARMA模型非因果空间预测滤波(英文)

常规频域预测滤波方法是建立在自回归(autoregressive,AR)模型基础上的,这导致滤波过程中前后假设的不一致,即首先利用源噪声的假设计算误差剖面,却又将其作为可加噪声而从原始剖面中减去来得到有效信号。本文通过建立自回归-滑动平均(autoregres sive/moving-average,ARMA)模型,首先求解非因果预测误差滤波算子,然后利用自反褶积形式投影滤波过程估计可加噪声,进而达到去除随机噪声目的。此过程有效避免了基于AR模型产生的不一致性。在此基础上,将一维ARMA模型扩展到二维空间域,实现了基于二维ARMA模型频域非因果空间预测滤波在三维地震资料随机噪声衰减中的应用。模型试验与实际资料处理表明该方法在很好保留反射信息同时,压制随机噪声更加彻底,明显优于常规频域预测去噪方法。     

A comparison of two bivariate extreme value distributions

There are two distinct bivariate extreme value distributions constructed from Gumbel marginals, namely Gumbel mixed (GM) model and Gumbel logistic (GL) model. These two models have completely different structures and their dependence ranges are different. The product-moment correlation coefficient for the former is [0,2/3] and the latter is [0,1]. It is natural to ask which one is more appropriate for representing the joint probabilistic behavior of two correlated Gumbel-distributed variables. This study compares these two models by numerical experiments. The comparison is based on that: (i) if the two distribution models are identical, then the joint probability and the joint return period computed by the GM model should be the same as those by the GL model; and (ii) if a selected distribution is the true distribution from which sample data are drawn, then the probabilities computed by the theoretical model should provide a good fit to empirical ones. Comparison results indicate that in the range of correlation coefficient [0,2/3], both models provide identical joint probabilities and joint return periods, and both indicate a good fit to empirical probabilities; while for (2/3,1), only the Gumbel logistic model can be used.     

Gravity effect calculation of three-dimensional linear density distribution and its application

An algorithm for calculating gravity effect of three-dimensional (3D) linear density distribution is presented in this paper. The linear continuous density distribution is represented with 3D grid model, which has a resemblance to the velocity model used in some seismic tomography codes. The consensus in representation method of density model and velocity model facilitates the seismic-gravity-integrated interpretation or simultaneous inversion. The numerical test of synthetic data shows that although the analytical gravity formula for linear density distribution is more complex than that for piecewise constant density distribution, it takes less time to calculate the gravity effect with linear density model than that with piecewise constant density model. In addition, this method is used in the integrated interpretation of 3D seismological tomography and gravity data in Dabie Mountain area.     

Analysis of extreme rainfall using the log logistic distribution

Computer-intensive methods are used to examine the fit of the log logistic distribution to annual maxima of Irish rainfall. The characteristics of the L-moment solutions are examined by using the conventional bootstrap on the data and by random sampling within the ellipse of concentration of the parameter estimates. A statistical method of examining uncertainty is provided by the maximum product of spacings solution. Factors derived from random division of an interval are proposed for estimation of short-duration falls for which no data are available.     

Interrelation among several important links in seismic risk analysis

Introduction In the probability analysis method of seismic risk considering time-space inhomogeneity of seismic activity and adopted commonly in China (State Seismological Bureau, 1996) (called in-homogeneous distribution model for short), the division of seismic statistical regions, delimitation of potential seismic sources and estimation of seismicity parameters are the main links that affect significantly the estimation of ground motion parameters of a site. HUANG and WU (2005) studied …     

龙门山和成都地震构造区的划分

新编制的地震动参数区划图采用了潜在震源区三级划分方案,以体现背景地震活动空间分布的不均匀性,并在地震构造区内归纳出统一的地震构造模型.本文根据西南地区潜在震源区三级划分的成果,分析了龙门山地震统计区内的龙门山和成都地震构造区的基本特征,历史地震活动强度及频度,主要活动构造的构造变形样式,建立了地震构造区的发震构造模型,确定了构造区的本底地震及划分构造源的地震构造标志.同时,提出了确定背景源空间分布函数的简单方法.