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Prediction framework in a distributed lag model with a target function: an application to global warming data Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-21 Nimet Özbay, Selma Toker
Due to the nature of the distributed lag model, researchers are likely to encounter the problem of multicollinearity in this model. Biased estimation techniques, one of which is Almon ridge estimation, are alternatively considered instead of Almon estimation with the aim of recovering the multicollinearity. Although estimation performance is often taken into consideration, predictive performance is
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A constrained-memory stress release model (CM-SRM) for the earthquake occurrence in the Corinth Gulf (Greece) Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-10 Ourania Mangira, Georgios Vasiliadis, George Tsaklidis, Eleftheria Papadimitriou
The complexity of seismogenesis requires the development of stochastic models, the application of which aims to improve our understanding on the seismic process and the associated underlying mechanisms. Seismogenesis in the Corinth Gulf (Greece) is modeled through a Constrained-Memory Stress Release Model (CM-SRM), which combines the gradual increase of the strain energy due to continuous slow tectonic
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Measuring the impact of higher education on environmental pollution: new evidence from thirty provinces in China Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-10 Hui Li, Shoukat Iqbal Khattak, Manzoor Ahmad
The study reported in this article investigated the relationship between higher education and environmental sustainability with control variables including foreign direct investment, electricity consumption, population, and gross domestic product from 30 provinces in China during the 2000–2018 period. The data were analyzed with cross-sectional dependency tests, panel unit-root tests, Kao cointegration
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Neyman–Scott process with alpha-skew-normal clusters Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-08 Nader Najari, Mohammad Q. Vahidi Asl
The Neyman–Scott processes introduced so far assume a symmetric distribution for the positions of the offspring points and this makes them inappropriate for modelling the skewed and bimodal clustered patterns and is a hindrance in fitting them to data that exhibit skewness or bimodality. In this paper, we apply the bivariate alpha-skew-normal distribution to the locations of the offspring points and
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Analysing the relationship between district heating demand and weather conditions through conditional mixture copula Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-06 F. Marta L. Di Lascio, Andrea Menapace, Maurizio Righetti
Efficient energy production and distribution systems are urgently needed to reduce world climate change. Since modern district heating systems are sustainable energy distribution services that exploit renewable sources and avoid energy waste, in-depth knowledge of thermal energy demand, which is mainly affected by weather conditions, is essential to enhance heat production schedules. We hence propose
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Assessing competition among species through simultaneously modeling marginal counts and respective proportions Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-02 Xingde Duan, Renjun Ma
Evolution processes of multiple competitive and non-competitive species have traditionally been handled using different methods. In particular, evolution processes of multiple competitive species have usually been evaluated by the continuous and discrete proportions analysis; however, such evolution processes cannot be solely characterized by their relative proportions in practice. In this paper, we
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Comparing methods to estimate the proportion of turbine-induced bird and bat mortality in the search area under a road and pad search protocol Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-11-30 Joseph Duggan Maurer, Manuela Huso, Daniel Dalthorp, Lisa Madsen, Claudio Fuentes
Estimating bird and bat mortality at wind facilities typically involves searching for carcasses on the ground near turbines. Some fraction of carcasses inevitably lie outside the search plots, and accurate mortality estimation requires accounting for those carcasses using models to extrapolate from searched to unsearched areas. Such models should account for variation in carcass density with distance
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Marked spatio-temporal point patterns, periodicity analysis and earthquakes: an analytical extension including hypocenter depth Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-11-09 Pierre Dutilleul, Christopher W. Johnson, Roland Bürgmann
The longitude, latitude and depth of the hypocenter in 3-D space and the date and time of rupture makes an earthquake a “point” in a spatio-temporal point pattern, observed over a region and months, years or decades. The magnitude of earthquakes marks the point pattern, as would hypocenter depth do if only the longitude and latitude of epicenters were used for location in 2-D space. Stochastic declustering
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Bayesian predictive model selection in circular random effects models with applications in ecological and environmental studies Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-26 Onur Camli, Zeynep Kalaylioglu
In this paper we present a detailed comparison of the prediction error based model selection criteria in circular random effects models. The study is primarily motivated by the need for an understanding of their performance in real life ecological and environmental applications. Prediction errors are based on posterior predictive distributions and the model selection methods are adjusted for the circular
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Financial development, globalization and ecological footprint in G7: further evidence from threshold cointegration and fractional frequency causality tests Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-26 Ugur Korkut Pata, Veli Yilanci
This paper empirically explores the dynamic relationships between financial development, globalization, energy consumption, economic growth, and ecological footprint in G7 countries over the period 1980–2015. Using a recently introduced threshold cointegration test with an endogenous structural break, the paper aims primarily to determine the effects of financial development and globalization on environmental
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Estimating historic movement of a climatological variable from a pair of misaligned functional data sets Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-15 Dibyendu Bhaumik, Debasis Sengupta
We consider the problem of estimating the mean function from a pair of paleoclimatic functional data sets after one of them has been registered with the other. We establish that registering one data set with respect to the other is the appropriate way to formulate this problem. This is in contrast with estimation of the mean function on a ‘central’ time scale that is preferred in the analysis of multiple
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Forecasting the Yellow River runoff based on functional data analysis methods Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-10 Ting Wang, Yingchun Zhou
This study examines the runoff prediction of each hydrometric station and each month in the mainstream of the Yellow River in China. From the perspective of functional data, the monthly runoff of each hydrometric station can be regarded as a function of both time and space. A sequence of such functions is formed by collecting the data over the years. We propose a new approach by combining the two-dimensional
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Spatial sampling for a rabies vaccination schedule in rural villages Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-10 Inger Fabris-Rotelli, Hayley Reynolds, Alfred Stein, Theodor Loots
Efforts are being made to contain rabies in Tanzania, reported in the southern highland regions, since 1954, and endemic in all districts in Tanzania currently. It has been determined that mass vaccination of at least \(70\%\) of a domestic animal population is most effective in reducing transmission of rabies. Current vaccination campaigns in Tanzanian villages have many administrative and logistical
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A puzzle over ecological footprint, energy consumption and economic growth: the case of Turkey Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-10-09 Ahmet Gülmez, Nurullah Altıntaş, Ünsal Ozan Kahraman
The paper investigates the non-linear causality from energy consumption and economic growth to ecological footprint for the case of Turkey by employing ARDL Models and ECM-Based Granger Causality over the period from 1961 to 2016. The major contribution of the article to the literature is that (i) the data period of the empirical analysis of the study is much longer than the one of the other studies
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A far-near sparse covariance model with application in climatology Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-09-18 Yi Li, Aidong Adam Ding
Teleconnection, the strong dependence between two distant locations, provides interesting information for discovering the structures in spatial data. While teleconnections are often sparse and estimated through sample correlations, there are also abundant correlations among nearby locations. We propose a far-near covariance model that simultaneously models the abundant short-distance dependencies and
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Statistical methods for forecasting daily snow depths and assessing trends in inter-annual snow depth dynamics Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-08-25 Jonathan Woody; QiQi Lu; James Livsey
This paper introduces a time-varying parameter regression model for modeling, forecasting, and assessing inter-annual trends in daily snow depths. The time-varying parameter regression is written in a simple state-space representation and forecasted using a Kalman filter. The recursive Kalman filter algorithm updates the time-varying parameter sequentially when a new data point becomes available and
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Cluster analysis methods applied to daily vessel location data to identify cooperative fishing among tuna purse-seiners Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-08-12 Cleridy E. Lennert-Cody, Mark N. Maunder, Marlon H. Román, Haikun Xu, Mihoko Minami, Jon Lopez
Management of large-scale pelagic fisheries relies heavily on fishery data to provide information on tuna population status because, for widely distributed populations, the cost of collecting survey data is often prohibitively high. However, fishery data typically do not provide direct information on interactions among fishing vessels, and thus methods of analysis often assume that vessels operate
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Lattice-based methods for regression and density estimation on complicated multidimensional regions Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-08-11 Ronald P. Barry; Julie McIntyre
This paper illustrates the use of diffusion kernels to estimate smooth density and regression functions defined on highly complex domains. We generalize the two-dimensional lattice-based estimators of Barry and McIntyre (2011) and McIntyre and Barry (2018) to estimate any function defined on a domain that may be embedded in \(\mathbb {R}^d\), \(d\ge 1\). Examples include function estimation on the
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Spatial and covariate-varying relationships among dominant tree species in Utah Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-08-07 Matthew J. Heaton; Candace Berrett; R. Justin DeRose; Matthew F. Bekker
The presence and establishment of a tree species at a particular spatial location is influenced by multiple physiological and environmental filters such as propagule pressure (seed availability), light and moisture availability, and slope and elevation. However, a less understood environmental filter to species-specific establishment is competition or facilitation between dominant tree species. For
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Computationally simple anisotropic lattice covariograms Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-07-31 Dean Koch, Subhash Lele, Mark A. Lewis
When working with contemporary spatial ecological datasets, statistical modellers are often confronted by two major challenges: (I) the need for covariance models with the flexibility to accommodate directional patterns of anisotropy; and (II) the computational effort demanded by high-dimensional inverse and determinant problems involving the covariance matrix \(\vec {V}\). In the case of rectangular
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Geostatistics under preferential sampling in the presence of local repulsion effects Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-07-27 Gustavo da Silva Ferreira
This paper presents an extension of the Geostatistical model under preferential sampling in order to accommodate possible local repulsion effects. This local repulsion can be caused by the researcher in charge of collecting data who, after observing the stochastic process of interest in a specific location, avoids collecting new samples near this place. Proceeding in this way, the resulting sampling
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Update of intensity–duration–frequency curves for Kuwait due to extreme flash floods Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-07-24 Dawod Aldosari; Jaber Almedeij; Abdullah A. Alsumaiei
Flash floods have devastating power due to their high rainfall intensities and short durations, causing serious damage to infrastructure and human life. Recent observations in the desert environment of Kuwait witnessed an increase in rainfall extremes, and the currently adopted intensity–duration–frequency (IDF) curves constructed three decades ago did not produce reliable design frequencies for existing
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A fuzzy goal programming with interval target model and its application to the decision problem of renewable energy planning Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-07-14 Amin Hocine; Mohammed Seghir Guellil; Eyup Dogan; Samir Ghouali; Noureddine Kouaissah
Optimizing sustainable renewable energy portfolios is one of the most complicated decision making problems in energy policy planning. This process involves meeting the decision maker’s preferences, which can be uncertain, while considering several conflicting criteria, such as environmental, societal, and economic impact. In this paper, rather than using existing techniques, a novel multi-objective
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Estimating population abundance using counts from an auxiliary population Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-07-14 Matthew R. P. Parker; Vivian Pattison; Laura L. E. Cowen
We develop a new method for estimating population abundance for notoriously difficult to count populations. This is made possible using an easy to count auxiliary population with a known link to the target population under the framework of a layered hidden Markov model. We apply the new methods to estimate the breeding population of an Ancient Murrelet seabird colony, using Ancient Murrelet chicks
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Improved prediction for a spatio-temporal model Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-30 Gen Nowak, A. H. Welsh
We investigate a framework for improving predictions from models for spatio-temporal data. The framework is based on minimising the mean squared prediction error and can be applied to many models. We applied the framework to a model for monthly rainfall data in the Murray-Darling Basin in Australia. Across a range of prediction situations, we improved the predictive accuracy compared to predictions
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Modelling non-proportional hazard for survival data with different systematic components Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-30 Fábio Prataviera; Selene M. C. Loibel; Kathleen F. Grego; Edwin M. M. Ortega; Gauss M. Cordeiro
We propose a new extended regression model based on the logarithm of the generalized odd log-logistic Weibull distribution with four systematic components for the analysis of survival data. This regression model can be very useful and could give more realistic fits than other special regression models. We obtain the maximum likelihood estimates of the model parameters for censored data and address
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Estimating total species using a weighted combination of expected mixture distribution component counts Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-27 Konstantin Shestopaloff; Wei Xu; Michael D. Escobar
In this paper we present a weighted mixture distribution component counts (MDCC) approach for estimating total number of species. The proposed method combines conditional estimates of component counts from several candidate mixture distributions and uses bootstrap for confidence interval estimation. The distribution specification is flexible and can be adjusted to suit a variety of datasets. Smoothing
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A spatiotemporal Richards–Schnute growth model and its estimation when data are collected through length-stratified sampling Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-13 Nan Zheng; Noel Cadigan; M. Joanne Morgan
We propose a spatiotemporal generalized von Bertalanffy (vonB) growth model that also includes between-individual (BI) variation and male/female correlation. The generalized vonB model includes the effect of maturation on growth. The model and the methodology are applied to a long time-series of survey observations of age and length for American plaice on the Grand Bank off the northeast coast of Canada
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Cointegration and causality: considering Iberian economic activity sectors to test the environmental Kuznets curve hypothesis Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-06 Victor Moutinho; Mara Madaleno; João Paulo Bento
Few studies have attempted to study the environmental Kuznets curve (EKC) hypothesis at the individual sector level using more than one sector at once. This paper investigates the existence of the EKC hypothesis in the Iberian countries (Portugal and Spain) using thirteen economic activity sectors for each, analyzing each individual sector’s cointegration and causality relationships considering carbon
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Modelling dependence structures of extreme wind speed using bivariate distribution: a Bayesian approach Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-06-04 Tadele Akeba Diriba; Legesse Kassa Debusho; Joel Ondego Botai
When investigating extremes of weather variables, it is seldom that a single weather station determines the damage, and extremes may be caused from the combined behaviour of several weather stations. To investigate joint dependence of extreme wind speed, a bivariate generalised extreme value distribution (BGEVD) was considered from frequentist and Bayesian approaches to analyse the extremes of component-wise
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Accounting for multiple testing in the analysis of spatio-temporal environmental data Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-05-12 José Cortés; Miguel Mahecha; Markus Reichstein; Alexander Brenning
The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, with a hypothesis test being performed for each grid cell. When the whole image or a set of grid cells are analyzed for a global effect, the problem of multiple testing arises. When no global effect is present, we expect \( \alpha \)% of all grid
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Generalised Additive Models and Random Forest Approach as effective methods for predictive species density and functional species richness Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-04-29 Jakub Z. Kosicki
Species distribution modelling (SDM) is a family of statistical methods where species occurrence/density/richness are combined with environmental predictors to create predictive spatial models of species distribution. However, it often turns out that due to complex multi-level interactions between predictors and the response function, different types of models can detect different numbers of important
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Mark recapture distance sampling: using acoustics to estimate the fraction of dolphins missed by observers during shipboard line-transect surveys Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-04-04 Shannon Rankin; Cornelia Oedekoven; Frederick Archer
Cetacean abundance estimation often relies on distance sampling methods using shipboard visual line-transect surveys, which assumes that all animals on the trackline are detected and that the detection of animals decreases with increasing distance from the trackline. Mark–Recapture Distance Sampling (MRDS) typically employs a secondary visual observation team and may be used to identify the fraction
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Coupling coordination measurement of environmental governance: case of China Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-04-03 Yiqin Tan; Yuqing Geng
The results show that a comprehensive evaluation system consisting of natural resources, pollution response, government management, and legal involvement can systematically assess the coupling coordination degree (CCD) of environmental governance. The information entropy weight (IEW) method and technique for order preference by similarity to an ideal solution (TOPSIS) are jointly used to analyze the
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Innovation, foreign direct investment (FDI), and the energy–pollution–growth nexus in OECD region: a simultaneous equation modeling approach Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-03-27 Manzoor Ahmad; Shoukat Iqbal Khattak; Anwar Khan; Zia Ur Rahman
The paper proposes a new perspective in the environmental and resource economics literature by examining innovation (measured by R&D expenditures), FDI (measured by country–country technology transfer), and energy–environment–growth nexus. Using simultaneous equation modelling (SEMs), three econometric functions were formulated for production, energy consumption, and environmental pollution with GDP
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On spline-based approaches to spatial linear regression for geostatistical data Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-03-10 Guilherme Ludwig; Jun Zhu; Perla Reyes; Chun-Shu Chen; Shawn P. Conley
For spatial linear regression, the traditional approach to capture spatial dependence is to use a parametric linear mixed-effects model. Spline surfaces can be used as an alternative to capture spatial variability, giving rise to a semiparametric method that does not require the specification of a parametric covariance structure. The spline component in such a semiparametric method, however, impacts
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Chao’s lower bound estimator and the size of the Pleiades Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-02-15 Dankmar Böhning
In this note we would like to point out that the lower bound estimator of the frequency of hidden units in a target population, developed by Chao in ecology, was developed independently in astro-physics and has been used to estimate the size of flare stars in the Pleiades.
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Estimation of rare and clustered population mean using stratified adaptive cluster sampling Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-01-28 Muhammad Nouman Qureshi; Cem Kadilar; Muhammad Hanif
For many clustered populations, the prior information on an initial stratification exists but the exact pattern of the population concentration may not be predicted. Under this situation, the stratified adaptive cluster sampling (SACS) may provide more efficient estimates than the other conventional sampling designs for the estimation of rare and clustered population parameters. For practical interest
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Modeling and simulation study of the stoichiometric niche space and niche overlap based on the copula method Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-01-09 Shaoqian Huang; Qi Zhou; Lianchao Gu; Hongqing Wang; Guangming Zhang
To qualify niche space and niche overlap, the current methods are based on a strict assumption of the normal distribution and restrict dependence to the linear structure between resource axes. In this study, we propose a new method for measuring the stoichiometric niche space and niche overlap based on copula theory. Our method does not require the resource axes to obey the multivariate normal distribution
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On function-on-function regression: partial least squares approach Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-01-07 Ufuk Beyaztas; Han Lin Shang
Functional data analysis tools, such as function-on-function regression models, have received considerable attention in various scientific fields because of their observed high-dimensional and complex data structures. Several statistical procedures, including least squares, maximum likelihood, and maximum penalized likelihood, have been proposed to estimate such function-on-function regression models
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Statistical inference using stratified judgment post-stratified samples from finite populations Environ. Ecol. Stat. (IF 0.981) Pub Date : 2020-01-07 Omer Ozturk; Konul Bayramoglu Kavlak
This paper develops statistical inference for population mean and total using stratified judgment post-stratified (SJPS) samples. The SJPS design selects a judgment post-stratified sample from each stratum. Hence, in addition to stratum structure, it induces additional ranking structure within stratum samples. SJPS is constructed from a finite population using either a with or without replacement sampling
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Robust ridge regression for estimating the effects of correlated gene expressions on phenotypic traits Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-12-26 Hirofumi Michimae; Masatoashi Matsunami; Takeshi Emura
Statistical packages such as edgeR and DESeq are intended to detect genes that are relevant to phenotypic traits and diseases. A few studies have also modeled the relationships between gene expressions and traits. In the presence of multicollinearity and outliers, which are unavoidable in genetic data, the robust ridge regression estimator can be applied with the trait value as the response variable
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Drivers of carbon dioxide emissions: an empirical investigation using hierarchical and non-hierarchical clustering methods Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-12-18 John Inekwe; Elizabeth Ann Maharaj; Mita Bhattacharya
The mitigation of CO2 emissions requires a global effort with common but differentiated responsibilities. In this paper, we identify clusters of CO2 emissions across 72 countries. First, using the stochastic version of the IPAT and employing the dynamic common correlated effects technique, we identify three key determinants affecting CO2 emissions (non-renewables, population, and real GDP). In the
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Model-averaged confidence distributions Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-11-22 David Fletcher; Peter W. Dillingham; Jiaxu Zeng
Model averaging is commonly used to allow for model uncertainty in parameter estimation. As well as providing a point estimate that is a natural compromise between the estimates from different models, it also provides confidence intervals with better coverage properties, compared to those based on a single best model. In recent years, the concept of a confidence distribution has been promoted as a
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Quantifying the uncertainty of variance partitioning estimates of ecological datasets Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-11-14 Matthias M. Fischer
An important objective of experimental biology is the quantification of the relationship between sets of predictor and response variables, a statistical analysis often termed variance partitioning (VP). In this paper, a series of simulations is presented, aiming to generate quantitative estimates of the expected statistical uncertainty of VP analyses. We demonstrate scenarios with considerable uncertainty
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Spatiotemporal calibration of atmospheric nitrogen dioxide concentration estimates from an air quality model for Connecticut Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-11-02 Owais Gilani; Lisa A. McKay; Timothy G. Gregoire; Yongtao Guan; Brian P. Leaderer; Theodore R. Holford
A spatiotemporal calibration and resolution refinement model was fitted to calibrate nitrogen dioxide (\(\hbox {NO}_2\)) concentration estimates from the Community Multiscale Air Quality (CMAQ) model, using two sources of observed data on \(\hbox {NO}_2\) that differed in their spatial and temporal resolutions. To refine the spatial resolution of the CMAQ model estimates, we leveraged information using
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The role of tourism growth in generating additional energy consumption: empirical evidence from major tourist destinations Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-10-11 Salih Katircioglu; Korhan K. Gokmenoglu; Baris Memduh Eren
This study investigates the role of tourism growth in generating additional energy consumption in the case of major tourist countries. Panel data that range from 1995 to 2014 have thus been constructed. Significant results of this study confirm long term economic effects of tourism growth in energy usage in tourist destinations; tourism exerts positively significant but inelastic effects on the overall
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Estimation and inference for upper hinge regression models Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-10-04 Adam Elder; Youyi Fong
We introduce a new type of threshold regression models called upper hinge models. Under this type of threshold models, there only exists an association between the predictor of interest and the outcome when the predictor is less than some threshold value. Just like hinge models, upper hinge models can be seen as a special case of the more general segmented or two-phase regression models. The importance
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To reduce or not to reduce: a study on spatio-temporal surveillance Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-09-13 Junzhuo Chen; Chuljin Park; Seong-Hee Kim; Yao Xie
The majority of control charts based on scan statistics for spatio-temporal surveillance use full observation vectors. In high-dimensional applications, dimension-reduction techniques are usually applied. Typically, the dimension reduction is conducted as a post-processing step rather than in the data acquisition stage and thus, a full sample covariance matrix is required. When the dimensionality of
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Fuzzy comprehensive evaluation of the disaster reduction ability of an ethnic minority accumulation area based on an analytic hierarchy process Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-09-13 Xiaoxiao Wang; Ruiting Shi; Yuting Lu; Ying Zhou
In order to promote the construction of disaster prevention and reduction of ethnic minority aggregation areas, in this study the Qijiawan community of the Hui people in Nanjing was taken as an example in order to build an evaluation index system of the disaster reduction ability of ethnic minority aggregation areas. In the research process, data were collected in the form of expert scores, the weights
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A Support Vector Machine approach for predicting progress toward environmental sustainability from information and communication technology and human development Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-09-10 Milena Lipovina-Božović; Ljiljana Kašćelan; Vladimir Kašćelan
Human activities are increasingly affecting the planet and its sustainability by degrading and damaging the environment. The literature on this topic has demonstrated that Information and Communications Technology (ICT) and human development (HD) are important promoters of progress towards environmental sustainability. The impact of these factors is most often examined by using standard regression
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Investigating the association between indoor radon concentrations and some potential influencing factors through a profile regression approach Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-09-05 Lara Fontanella; Luigi Ippoliti; Annalina Sarra; Eugenia Nissi; Sergio Palermi
Radon-222 is a naturally occurring radioactive gas arising from the decay of Uranium-238 present in the earth’s crust. The knowledge of the radon effects on human health is generating a growing attention by national and international authorities aimed at assessing the exposure of people to this radioactive gas and identifying building types and geographic areas where high indoor radon concentrations
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Using a non-homogeneous Poisson model with spatial anisotropy and change-points to study air pollution data Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-06-15 Eliane R. Rodrigues; Geoff Nicholls; Mario H. Tarumoto; Guadalupe Tzintzun
A non-homogeneous Poisson process is used to study the rate at which a pollutant’s concentration exceeds a given threshold of interest. An anisotropic spatial model is imposed on the parameters of the Poisson intensity function. The main contribution here is to allow the presence of change-points in time since the data may behave differently for different time frames in a given observational period
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A new probability model with application to heavy-tailed hydrological data Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-05-31 Tassaddaq Hussain; Hassan S. Bakouch; Christophe Chesneau
Because of the dramatic changes that are being observed in the climatic conditions of the world, such as excess of rains, drought and huge floods, we introduce a versatile hydrologic probability model with three parameters. The proposed model is a combination of the Lomax and generalized Weibull distributions based on an exponent odd function. Main properties of the distribution are obtained, such
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Jointly estimating survival and mortality: integrating recapture and recovery data from complex multiple predator systems Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-03-22 Quinn Payton; Nathan J. Hostetter; Allen F. Evans
Identifying where, when, and how many animals live and die over time is principal to understanding factors that influence population dynamics. Capture–recapture–recovery (CRR) models are widely used to estimate animal survival and, in many cases, quantify specific causes of mortality (e.g., harvest, predation, starvation). However, the restrictive CRR framework can inhibit the consideration and inclusion
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Modelling relationships between socioeconomy, landscape and water flows in Mediterranean agroecosystems: a case study in Adra catchment (Spain) using Bayesian networks Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-03-05 Rosa F. Ropero; Rafael Rumí; Pedro A. Aguilera
In Mediterranean areas, the co-evolution between social and natural systems has given rise to heterogeneous and complex systems of interactions called agroecosystems, in which strong relationships between socioeconomy, landscape and water flows have been identified. In this context, water resources management is a prominent area of research, particularly in semi-arid conditions, where a special set
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A history matching approach for calibrating hydrological models Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-02-27 Natalia V. Bhattacharjee; Pritam Ranjan; Abhyuday Mandal; Ernest W. Tollner
Calibration of hydrological time-series models is a challenging task since these models give a wide spectrum of output series and calibration procedures require significant amount of time. From a statistical standpoint, this model parameter estimation problem simplifies to finding an inverse solution of a computer model that generates pre-specified time-series output (i.e., realistic output series)
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Bayesian-based survival analysis: inferring time to death in host-pathogen interactions Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-02-08 Sama Shrestha; Bret D. Elderd; Vanja Dukic
The standard approach to modeling survival times, or more generally, time to event data, is often based on parametric assumptions that may not fit the data collected well. One of the goals of this article is to discuss and compare several commonly used parametric and non-parametric, as well as a Bayesian semi-parametric method for survival data. We do so in the context of the data from an experimental
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Modeling Aedes aegypti trap data with unobserved components Environ. Ecol. Stat. (IF 0.981) Pub Date : 2019-01-14 Thiago Rezende dos Santos
Several models have been proposed to describe the population dynamics of Aedes aegypti. Intuitive interpretation of model parameters and simplicity are some of the main characteristics of mechanistic models. Another possibility is the use of statistical models, which have their advantages but are not easy to interpret. The state-space model (SSM), also known as a mechanistic time series model, incorporates
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Benchmarking a triplet of official estimates Environ. Ecol. Stat. (IF 0.981) Pub Date : 2018-11-21 Andreea L. Erciulescu; Nathan B. Cruze; Balgobin Nandram
The publication of official statistics at different levels of aggregation requires a benchmarking step. Difficulties arise when a benchmarking method needs to be applied to a triplet of related estimates, at multiple stages of aggregation. For ratios of totals, external benchmarking constraints for the triplet (numerator, denominator, ratio) are that the weighted sum of denominator/numerator/ratio
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