Parameter estimate for three-parameter kappa distribution using LHmoments approach

The method of higher-order L-moments (LH-moment) was proposed as a more robust alternative compared to classical L-moments to characterize extreme events. The new derivation will be done for Mielke-Johnson’s Kappa and Three-Parameters Kappa Type-II (K3D-II) distributions based on the LH-moments approach. The data of maximum monthly rainfall for Embong station in Terengganu were used as a case study. The analyses were conducted using the classical L-moments method with η=0 and LH-moments methods with η=1, η=2, η=3 and η=4 for a complete data series and upper parts of the distributions. The most suitable distributions were determined based on the Mean Absolute Deviation Index (MADI), Mean Square Deviation Index (MSDI), and Correlation (r). Also, L-moment and LH-moment ratio diagrams were used to represent visual proofs of the results. The analysis showed that LH-moments methods at a higher order of K3D-II distribution best fit the data of maximum monthly rainfalls for the Embong station for the upper parts of the distribution compared to L-moments. The results also proved that whenever η increases, LH-moments reflect more and more characteristics of the upper part of the distribution. This seems to suggest that LH-moments estimates for the upper part of the distribution events are superior to L-moments in fitting the data of maximum monthly rainfalls.

Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

In this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.

On the Adequacy of Some Low-Order Moments Method to Simulate Certain Particle Removal Processes

The population balance is an indispensable tool for studying colloidal, aerosol, and, in general, particulate systems. The need to incorporate spatial variation (imposed by flow) to it invokes the reduction of its complexity and degrees of freedom. It has been shown in the past that the method of moments and, in particular, the log-normal approximation can serve this purpose for certain phenomena and mechanisms. However, it is not adequate to treat gravitational deposition. In the present work, the ability of the particular method to treat diffusional and convective diffusional depositions relevant to colloid systems is studied in detail.

Analysis of Volcanic Thermohaline Fluctuations of Tagoro Submarine Volcano (El Hierro Island, Canary Islands, Spain)

Temperature and conductivity fluctuations caused by the hydrothermal emissions released during the degasification stage of the Tagoro submarine volcano (Canary Islands, Spain) have been analysed as a robust proxy for characterising and forecasting the activity of the system. A total of 21 conductivity-temperature-depth time series were gathered on a regular high-resolution grid over the main crater of Tagoro volcano. Temperature and conductivity time series, as manifestations of stochastic events, were investigated in terms of variance and analysed by the Generalised Moments Method (GMM). GMM provides the statistical moments, the structure functions of a process whose shape is an indicator of the underlying stochastic mechanisms and the state of activity of the submarine volcano. Our findings confirm an active hydrothermal process in the submarine volcano with a sub-normal behaviour resulting from anti-persistent fluctuations in time. Its hydrothermal emissions are classified as multifractal processes whose structure functions present a crossover between two time scales. In the shorter time scale, findings point to the multiplicative action of two random processes, hydrothermal vents, which carries those fluctuations driving the circulation over the crater, and the overlying aquatic environment. Given that both temperature and conductivity fluctuations are nonstationary, Tagoro submarine volcano can be characterised as an open system exchanging energy to its surroundings.

The Hydrothermal Vent Field at the Eastern Edge of the Hellenic Volcanic Arc: The Avyssos Caldera (Nisyros)

Almost three-quarters of known volcanic activity on Earth occurs in underwater locations. The presence of active hydrothermal vent fields in such environments is a potential natural hazard for the environment, society, and economy. Despite its importance for risk assessment and risk mitigation, the monitoring of volcanic activity is impeded by the remoteness and the extreme conditions of many underwater volcanoes. The morphology and the activity of the submarine caldera, Avyssos, at the northern part of Nisyros volcano in the South Aegean Sea (Greece), were studied using a remotely operated underwater vehicle. The recorded time series of temperature and conductivity over the submarine volcano have been analyzed in terms of the Generalized Moments Method. This type of analysis can be used as an indicator for the state of activity of a submarine volcano. Here, we expand the work conducted for the first time in 2018. We present the findings of the geological exploration and the mathematical analysis, obtained from the data collected in October 2010. The temperature and conductivity time series show minor fluctuations in a rather stable environment. Based on these results, the impact of developing appropriate mechanisms and policies to avoid the associated natural hazard is expected to be important.

Revision of Frequency Estimates of Extreme Precipitation Based on the Annual Maximum Series in the Jiangsu Province in China

Frequency estimates of extreme precipitation are revised using a regional L-moments method based on the annual maximum series and Chow’s equation at lower return periods for the Jiangsu area in China. First, the study area is divided into five homogeneous regions, and the optimum distribution for each region is determined by an integrative assessment. Second, underestimation of quantiles and the applicability of Chow’s equation are verified. The results show that quantiles are underestimated based on the annual maximum series, and that Chow’s formula is applicable for the study area. Next, two methods are used to correct the underestimation of frequency estimation. A set of rational and reliable frequency estimations is obtained using the regional L-moments method and the two revised methods, which can indirectly provide a robust basis for flood control and water resource management. This study extends previous works by verifying underestimation of the quantiles and the provision of two improved methods for obtaining reliable quantile estimations of extreme precipitation at lower recurrence intervals, especially in solving reliable estimates for a 1-year return period from the integral lower limit of the frequency distribution.

Leader Nationalism, Ethnic Identity, and Terrorist Violence

Whether or not nationalism fuels terrorist violence by ethnic groups is an important yet underexplored research question. This study offers a theoretical argument, empirical analysis and a case study. When political leaders such as presidents and prime ministers use nationalism to shore up legitimacy, they threaten the existence of disfavored ethnic groups. In turn, those groups are more likely to respond with terrorist attacks. The author tests this argument using a sample of 766 ethnic groups across 163 countries from 1970 to 2009. The multilevel mixed-effects negative binomial regression results provide evidence that leader nationalism is a significant driver of ethnic terrorism. The detrimental effect of nationalism remains the same after using a generalized method of moments method to account for possible reverse causality. A case study of Sinhalese nationalist leaders versus Tamil Tigers also supports the nationalism and terrorism nexus.