Bivariate Combinations Research Articles

Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment

AbstractQuantifying flood risk depends on accurate probability estimation, which is challenging due to non‐stationarity and the combined effects of multiple factors in a changing environment. The threat of compound flood risks may spread from coastal areas to inland basins, which have received less attention. In this study, a framework based on time‐varying copulas was introduced for the treatment of compound flood risk and bivariate design in non‐stationary environments. Archimedean copulas were developed to diagnose the non‐stationary trends of flood risk. Return periods, average annual reliabilities, and bivariate designs were estimated. Model uncertainty was analyzed by comparing the results for stationary and non‐stationary conditions. The case study investigated the extreme rainfall and water level series from the Qinhuai River Basin and the Yangtze River in China. The results showed that marginal distributions and correlations are non‐stationary in all bivariate combinations. Ignoring composite effects may lead to inappropriate quantification of flood risk. Excluding non‐stationarity may lead to risk over or underestimation. It showed the limitations of the 1‐day scale and quantified the uncertainty of non‐stationary models. This study provided a flood risk assessment framework in a changing environment and a risk‐based design technique, which is essential for climate change adaptation and water management.

Diversity of decapod crustaceans in a neotropical coastal lagoon interconnected with the sea/estuary

Coastal lagoons are aquatic environments that are located at the coast-sea interface. Ecologically important, they harbor a high abundance of macroinvertebrates, especially decapod crustaceans. Therefore, the present study investigated the influence of physical factors on the diversity of decapod macrocrustaceans in a Neotropical coastal lagoon and prepared a list of species, with emphasis on new occurrences for this habitat. The study was conducted from January/2013 to January/2014 in a Neotropical coastal lagoon, seasonally connected to the sea. Ecological indices were estimated to understand biotic diversity; in addition, correlations and type II regression were performed on bivariate combinations to assess the degree of interaction between biotic vs. abiotic variables related to lagoon hydrodynamics. Finally, a partial least squares regression was performed to assess such relationships in the multivariate scenario. Field observations revealed a period of interconnection between the lagoon and the sea/estuary in March and complete isolation in October. The most abundant taxa were Penaeus sp., Callinectes sp., C. danae, Pagurus criniticornis and Clibanarius sclopetarius. In the month before total isolation, greater general abundance was recorded, and in the following month, greater diversity, dominance and equitability were recorded. In the multivariate model, only Maximum Wind Gust, Hourly Wind Speed and Minimum Monthly Astronomical Tide were relevant to explain the biotic variations in the lagoon. These results demonstrate that wind and tide can act as proxies for the hydrodynamic analysis of the lagoon in relation to the biotic factors investigated, since they promote seasonal events of opening and isolation of connectivity, contributing to the transport of individuals by carrying water masses. Still, the coastal lagoon presented itself as a place of shelter and foraging for the biota, with emphasis on the genera Penaeus and Callinectes that use the lagoons to complete their life cycle in the sea-estuary transition. This study indicates that coastal lagoons are essential for the life cycle of coastal crustaceans and should be included in management actions to conserve these areas and Neotropical crustacean species.

Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins

Genetic improvement is a crucial tool to deal with the increasing demand for high quality, sustainably produced dairy. Breeding programs are based on genetic parameters, such as heritability and genetic correlations, for economically important traits in a population. In this study, we estimated population genetic parameters and genetic trends for 67 traits evaluated on heifers and first-lactation Canadian Holstein cows. The data consisted of approximately 500,000 records with pedigree information collected from 1980 to 2019. Genetic parameters were estimated using bivariate linear animal models under a Bayesian approach. Analyses for the 67 traits resulted in 2,211 bivariate combinations, from which the estimated genetic parameters are reported here. The most highly heritable traits were fat percent (0.66) and protein percent (0.69), followed by stature (0.47). Lowest heritabilities (0.01) were observed for disease-related traits, such as lameness and toe ulcer, and calf survival. The genetic correlations between gestation length, calf size, and calving ease measured on both heifer and cows were close to unity. On the other hand, traits such as body condition score and pin width, cystic ovaries and sole ulcer, rear teat placement, and toe ulcer were genetically unrelated. This study reports genetic parameters that have not been previously published for Canadian Holstein cows, and provides updates of those previously estimated. These estimates are useful for building new indexes, updating existing selection indexes, and for predicting correlated responses due to inclusion of novel traits in the breeding programs.

Expected shortfall assessment in commodity (L)ETF portfolios with semi-nonparametric specifications

ABSTRACTThis paper studies the risk assessment of semi-nonparametric (SNP) distributions for leveraged exchange trade funds, (L)ETFs. We applied the SNP model with dynamic conditional correlations (DCC) and EGARCH innovations, and implement recent techniques to backtest Expected Shortfall (ES) to portfolios formed by bivariate combinations of major (L)ETFs on metal (Gold and Silver) and energy (Oil and Gas) commodities. Results support that multivariate SNP-DCC model outperforms the Gaussian-DCC and provides accurate risk measures for commodity (L)ETFs.

Dynamic Relations of Consumer Prices: A Case Study of Recent Effects on the Japanese Headline CPI

<p>This study attempts to empirically examine the relations between the headline consumer price index (CPI) and several other CPIs in Japan by applying the vector error correction models (VECMs). Our investigations derive the following interesting findings. First, we reveal that as to our four combinations of the CPIs tested in this paper, 1) all variable coefficients in the cointegrating equations are statistically significant in our VECM models and the statistical significance is very strong. Thus, we understand that our four bivariate combinations of the CPIs tested in this paper are all strongly cointegrated and the VECM approach is very effective to capture the time-series effects of the categorized CPIs on the Japanese headline CPI. Further, we also find that 2) as far as judging by the results of our impulse response analyses, for the period from May 2011 to June 2015, the headline CPI for Japan is weakly or little affected by the CPI of energy and the CPI of food for Japan. We further clarify that 3) according to the results of our impulse response analyses, the Japanese headline CPI is positively affected by both the CPI of utilities for Japan and the CPI of transportation and communication expenses for Japan.</p>

On two families of bivariate distributions with exponential marginals: Aggregation and capital allocation

In this paper, we consider two main families of bivariate distributions with exponential marginals for a couple of random variables (X1,X2). More specifically, we derive closed-form expressions for the distribution of the sum S=X1+X2, the TVaR of S and the contributions of each risk under the TVaR-based allocation rule. The first family considered is a subset of the class of bivariate combinations of exponentials, more precisely, bivariate combinations of exponentials with exponential marginals. We show that several well-known bivariate exponential distributions are special cases of this family. The second family we investigate is a subset of the class of bivariate mixed Erlang distributions, namely bivariate mixed Erlang distributions with exponential marginals. For this second class of distributions, we propose a method based on the compound geometric representation of the exponential distribution to construct bivariate mixed Erlang distributions with exponential marginals. Notably, we show that this method not only leads to Moran–Downton’s bivariate exponential distribution, but also to a generalization of this bivariate distribution. Moreover, we also propose a method to construct bivariate mixed Erlang distributions with exponential marginals from any absolutely continuous bivariate distributions with exponential marginals. Inspired from Lee and Lin (2012), we show that the resulting bivariate distribution approximates the initial bivariate distribution and we highlight the advantages of such an approximation.

Total quality management success factors and their relationships with performance measures in the food industry: a Mauritian case study

This study was undertaken to identify factors needed for a successful implementation of a total quality management (TQM) programme in Mauritian food manufacturing companies (MFMC) and to evaluate their impact on operational performance (OP), quality performance (QP) and business performance (BP). Carrying out reliability test and validity tests like exploratory factor analysis with the data collected, valid and reliable constructs were determined. Using these constructs, a proposed model that consisted of the three performance measures; OP, QP and BP, and the identified success factors aggregated as TQM index was tested using structural equation modelling. Results showed that the constructs were valid and reliable, and all the bivariate combinations in the proposed model were significant (p 0.05). Removing these two pathways made the model fit. Hence, TQM index did not have a direct and significant effect on BP in this study.

Evolution of the international crude oil market mechanism

This study explains how the international crude oil market mechanism has evolved. It suggests a systematic approach to analyse the hypothesis of the integration of the international oil market, the structural changes in oil price movements and the benchmark role of specific crude, which have been separately discussed in previous studies. We analyse weekly spot prices of Dubai, Brent and West Texas Intermediate (WTI) from January 1997 to July 2012. First, the empirical results of the cointegration test taking a structural break into account show that all the bivariate combinations of these three crude oil prices are cointegrated and that most of the structural breaks occur in 2009. These cointegrating relationships thus indicate that the international crude oil market is integrated. Second, considering the structural breaks suggested by the cointegration test results and the timing of the price reversal between different crudes, the causal relationships before 2009 and those afterwards are compared. Before 2009, bidirectional causality is observed for all the bivariate combinations of the Dubai, Brent and WTI prices. However, the Dubai price unidirectionally causes the Brent and WTI prices thereafter. This result implies that the Dubai price has played a benchmark role in the international crude oil market since 2009.

The evidential value of microspectrophotometry measurements made for pen inks

Three colour systems, defined by the International Commission on Illumination (CIE), have been used to parametrise spectra from microspectrophotometry in the visible range for ten replicates of each of forty inks. The parametrised spectra were used to calculate a likelihood ratio (LR) for pairwise comparisons under the propositions implying that any ink from some suspect document came from the same pen, as that from a control document, versus, the converse proposition which implies the ink from the suspect document came from some other pen. Both univariate and bivariate likelihood ratios for each colour system were calculated. Empirical cross-entropy was selected as an appropriate measure of performance for each system. The bivariate combinations of the CIE-xyz colour system achieve the best results as well as a bivariate combination of a and b variables within the CIE-Lab colour system.

Continuous rainfall simulation: 2. A regionalized daily rainfall generation approach

This paper is the second of two in the current issue that presents a framework for simulating continuous (uninterrupted) rainfall sequences at both gaged and ungaged locations. The ultimate objective of the papers is to present a methodology for stochastically generating continuous subdaily rainfall sequences at any location such that the statistics at a range of aggregation scales are preserved. In this paper we complete the regionalized algorithm by adopting a rationale for generating daily sequences at any location by sampling daily rainfall records from “nearby” gages with statistically similar rainfall sequences.The approach consists of two distinct steps: first the identification of a set of locations with daily rainfall sequences that are statistically similar to the location of interest, and second the development of an algorithm to sample daily rainfall from those locations. In the first step, the similarity between all bivariate combinations of 2708 daily rainfall records across Australia were considered, and a logistic regression model was formulated to predict the similarity between stations as a function of a number of physiographic covariates. Based on the model results, a number of nearby locations with adequate daily rainfall records are identified for any ungaged location of interest (the “target” location), and then used as the basis for stochastically generating the daily rainfall sequences. The continuous simulation algorithm was tested at five locations where long historical daily rainfall records are available for comparison, and found to perform well in representing the distributional and dependence attributes of the observed daily record. These daily sequences were then used to disaggregate to a subdaily time step using the rainfall state‐based disaggregation approach described in the first paper, and found to provide a good representation of the continuous rainfall sequences at the location of interest.

International stock markets interactions and conditional correlations

This paper investigates the transmission of price and volatility spillovers across the US and European stock markets in bivariate combinations. The framework used encompasses the most popular multivariate GARCH models, with News Impact Surfaces employed for interpretation. By using synchronous data the dynamic conditional correlation model (Engle, R., 2002. Dynamic conditional correlation: a simple class of multivariate GARCH models. Journal of Business and Economic Statistics 20, 339–350) is found to best capture the relationships for over half of the bivariate combinations of markets. Other findings include volatility spillovers from the US to European markets, and a reverse spillover. In addition, the magnitude of the correlation between markets is higher not only for negative shocks in both markets, but also when a combination of shocks of opposite signs occurs.

Correlates to Traumatic Brain Injury in Nonhuman Primates

Traumatic brain injury (TBI) is a major health problem, both in terms of the economic cost to society and the survivor's quality of life. The development of devices to protect against TBI requires criteria that relate observed injury to measurements of head kinematics. The objective of this study is to find the best statistical correlates to impact-induced TBI in nonhuman primates using a qualified, self-consistent set of historical kinematic and TBI data from impact tests on nonhuman primates. A database was constructed and qualified from historical head impact tests on nonhuman primates. Multivariate logistic regression analysis with backwards stepwise elimination was performed. Variables considered are the peak rotational acceleration (Omegamax), the peak linear acceleration (Amax), and the number of impacts (N). Bivariate combinations of angular acceleration and the number of impacts are the best correlates to all modes of TBI considered, i.e., concussion, subarachnoid hemorrhage, brain contusion, and subdural hematoma. For a nonhuman primate with 100-g brain mass, the criteria that the probability of TBI is less than 10% by injury mode are:Concussion: OmegamaxN(0.84) < 70 krad/s/s SAH: OmegamaxN(0.70) < 160 krad/s/s Contusion: Omegamax N(0.35) < 160 krad/s/s SDH: Omegamax N(0.60) < 280 krad/s/s Based on this dataset, the best statistically based risk factor for all modes of TBI in nonhuman primates is the bivariate combination of rotational acceleration and number of impacts.

Representative Bivariate Percentiles for Anthropometric Design

This paper presents graphs which simplify the task of selecting bivariate anthropometric dimensional combinations which are to be representative of the design population. Data for the graphs are based on defining bivariate percentile pairs in a manner modeled after the techniques of defining univariate percentiles. The charts are presented in “Z” format and assume that the bivariate data are normally distributed. The charts and the method of defining bivariate percentile combinations should be of use in many areas of anthropometric design and evaluation including defining representative computer implemented manikins.

COMPUTER GENERATION OF HIGHLY SKEWED CORRELATED RANDOM VARIABLES

ABSTRACT A multivariate approach was previously developed for generating non-normal correlated random variables (Taylor and Bender, 1988, 1989). The method exactly preserves each univariate probability distribution; however, there may be cases where the correlations between variables are not preserved. The objective of this study was to empirically determine how well the multivariate approach preserves the correlations for highly skewed probability distributions. Three bivariate combinations were examined: (1) both distributions positively skewed, (2) both distributions negatively skewed, and (3) one positively and one negatively skewed. The multivariate method preserved the correlation between variables with excellent accuracy except for the case involving a mixture of positively and negatively skewed distributions in conjunction with high correlation. KEYWORDS. Probability distributions. Computer simulation..

The use of random F3 families for cross prediction in spring barley

SummaryRandom F3 families from six crosses typical of those being made in a spring barley breeding programme at the Scottish Crop Research Institute were used to rank the crosses on the basis of their predicted probabilities of exceeding a given standard for a number of characters. The predicted rankings were then compared with the observed rankings of the crosses based on observations of random inbred lines from the same crosses. The agreement between predicted and observed rankings was very good for single characters and good for bivariate combinations of the characters. The agreement for the bivariate combination of height and single plant yield was exact and the combination also appeared to be capable of accurately ranking crosses on the basis of height and plot yield.The practical considerations of using such a cross prediction technique in a cereal breeding programme are discussed. Results from this experiment suggest that single plant measurement could be replaced by measurements on progeny rows, thereby saving considerably on labour. Predictions could just be made on the most important characters in the breeder's model for the early identification of the best crosses but this is still an advance on the approach of making many crosses and assessing relatively few selections from each cross in yield trials.

Identification and isolation of subpopulations of pleural cells by multiparameter flow cytometry

Multiparameter flow cytometry was used to identify and sort subpopulations of cells from pleural cell populations harvested from the rat without employing special stains or fluorochrome-labeled monoclonal antibodies. Cell parameters measured included electronic volume, axial light loss, 90 degrees light scatter, and blue autofluorescence. Various bivariate combinations of these parameters were used to distinctly resolve pleural macrophages, eosinophils, mast cells, and lymphocytes. These subpopulations were separately sorted viably according to their unique electrooptical phenotypic characteristics in greater than 90% purity. Our multiparameter flow cytometric approach, accordingly, provides a means by which pleural cell subpopulations may be easily obtained for subsequent in vitro study. Moreover, the general strategy for identifying and isolating these subpopulations may be usefully extended to the identification and isolation of subpopulations of cells occurring in other complex cell mixtures.

Genetical investigations into β-glucan content in barley

Random inbred lines produced by doubled haploidy (DH) and single seed descent (SSD) have been used to investigate the genetics of β-glucan (gum) content in barley (Hordeum vulgare). Genetical analyses indicated that gum content is controlled by a simple additive genetic system. Significant negative genetic correlations were observed between β-glucan content, thousand grain weight and height in the DH samples. These correlations were much reduced in the SSD samples and would suggest linkage of the genes controlling these characters. The presence of repulsion linkages could be exploited in a barley breeding programme by producing F1 derived DH to generate recombinants with high thousand grain weight and low β-glucan content. Genetical parameters estimated from DH and F3 samples have successfully been used to predict the number of inbred lines transgressing the parental range for β-glucan content and bivariate combinations involving β-glucan.

Principal components for allometric analysis.

Logarithmic bivariate regression slopes and logarithmic principal component coefficient ratios are two methods for estimating allometry coefficients corresponding to a in the classic power formula Y = BXa. Both techniques depend on high correlation between variables. Interpretation is logically limited to the variables included in analysis. Principal components analysis depends also on relatively uniform intercorrelations; given this, it serves satisfactorily as a method for summarizing many bivariate combinations. Unmodified major principal component coefficients cannot represent scaling to body weight; rather, they represent scaling to a composite size vector which usually is highly correlated with body size or weight but has an unspecified allometry. Thus, the concepts of proportionality and of isometry must be kept distinct.

Analysis of a North Dakota Gallery Forest: Vegetation in Relation to Topographic and Soil Gradients

Vegetation—environment relationships were studied in forest stands located on slopes and a floodplain in northeastern North Dakota. Coverage values of all vascular plants and basal area, frequency, density, and mensuration data for tree species were obtained. A total of 109 species of vascular plants, 10 of mosses, and 15 of lichens are reported for the 40 plots studied. The three most important (based on importance value) overstory species are Quercus macrocarpa, Tilia americana, and Fraxinus pennsylvanica var. subintegerrima. Less important overstory species include Ulmus americana, Acer negundo, Populus tremuloides, and Betula papyrifera. Tree—ring analysis indicates that the present forest is less than 100 yr old. Correlation analyses were made between community characteristics of vegetation and the topographic parameters, slope inclination, aspect, and elevation. Principal component analysis and Swan—Dix—Wehrhahn ordination were used to establish five abstract community types. Environmental soil parameters measured for each soil horizon within the rooting zone include available water capacity; pH; electrical conductivity; cation exchange capacity; percentage organic matter; replaceable Ca, Mg, K, Na, Sr, and Mn; available P; and EDTA—extractable Al, Cu, Fe, Mn, Ni, Pb, Si, Sr, and Zn. Topographic and soil parameters were used for stepwise elimination multiple regressions to develop predictive equations for the distribution of plant species. Correlation analysis reveals that the basal area of trees and number and coverage values of herbaceous species is highest on lower elevations and south exposures. Whereas pronounced vegetation differences occur between slopes and the floodplain, the vegetation patterns on the slopes are continuous and overlapping. Based on the results from multiple regression analysis, gradients for potential solar beam irradiation, available water capacity, elevation, linear aspect, slope inclination, and replaceable K were established. By use of coverage values, ecological modalities of selected species are demonstrated along quantified gradients. Relationships of plots in several bivariate combinations show patterns of community type resembling those obtained by stand ordination.