-
High spatial resolution IoT based air PM measurement system Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-04-12 Ebru İçöz, Fasih M. Malik, Kutay İçöz
Air pollution is one of the global problems of the current era. According to World Health Organization more than 80% of the people living in metropolitan areas breathe air which exceeds the guideline limits. Particulate matter, the mixture of liquid and solid particles having diameters less than 10 μm, is one of the important pollutants in the air. The main source of the Particulate matter is mostly
-
Evaluation of CMIP5 models and ensemble climate projections using a Bayesian approach: a case study of the Upper Indus Basin, Pakistan Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-03-24 Firdos Khan, Jürgen Pilz, Shaukat Ali
The availability of a variety of Global Climate Models (GCMs) has increased the importance of the selection of suitable GCMs for impact assessment studies. In this study, we have used Bayesian Model Averaging (BMA) for GCM(s) selection and ensemble climate projection from the output of thirteen CMIP5 GCMs for the Upper Indus Basin (UIB), Pakistan. The results show that the ranking of the top best models
-
Is food production vulnerable to environmental degradation? A global analysis Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-03-24 Suet-Ling Ching, Kwang-Jing Yii, Cheong-Fatt Ng, Chee-Keong Choong, Lin-Sea Lau
The issue on whether food production has a severe impact on the environment has been receiving increased attention in recent years. By utilizing three different estimators, this paper investigates the effect of environmental degradation on food production underlying the Cobb–Douglas production function. We also test the role of R&D, capital and labour on food production. All three estimators provide
-
Maximum likelihood inference for the band-read error model for capture-recapture data with misidentification Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-03-24 Wei Zhang, Steven J. Price, Simon J. Bonner
Misidentification of animals is a common problem for many capture-recapture experiments. Considerably misleading inference may be obtained when traditional models are used for capture-recapture data with misidentification. In this paper, we investigate the so-called band-read error model for modeling misidentification, assuming that it is possible to identify one marked individual as another on each
-
Bayesian non-parametric detection heterogeneity in ecological models Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-03-22 Daniel Turek, Claudia Wehrhahn, Olivier Gimenez
Detection heterogeneity is inherent to ecological data, arising from factors such as varied terrain or weather conditions, inconsistent sampling effort, or heterogeneity of individuals themselves. Incorporating additional covariates into a statistical model is one approach for addressing heterogeneity, but there is no guarantee that any set of measurable covariates will adequately address the heterogeneity
-
Regression model under skew-normal error with applications in predicting groundwater arsenic level in the Mekong Delta Region Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-03-17 Uyen Huynh, Nabendu Pal, Man Nguyen
Recently there has been some renewed interest in skew-normal distribution (SND) because it provides a nice and natural generalization (in terms of accommodating skewed data) over the usual normal distribution. In this study we have used the SND error in a regression set-up, discussed a step by step approach on how to estimate all the model parameters, and show how naturally the resultant SND-based
-
Halton iterative partitioning master frames Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-02-17 Blair Robertson, Paul van Dam-Bates, Oliver Gansell
A spatial sampling design determines where sample locations are placed in a study area. To achieve reliable estimates of population characteristics, the spatial pattern of the sample should be similar to the underlying spatial pattern of the population. A reasonable assumption for natural resources is that nearby locations tend to have more similar response values than distant locations. Hence, sample
-
Modified information criterion for regular change point models based on confidence distribution Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-02-12 Suthakaran Ratnasingam, Wei Ning
In this article, we propose procedures based on the modified information criterion and the confidence distribution for detecting and estimating changes in a three-parameter Weibull distribution. Corresponding asymptotic results of the test statistic associated the detection procedure are established. Moreover, instead of only providing point estimates of change locations, the proposed estimation procedure
-
The measurement of green finance index and the development forecast of green finance in China Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-02-09 Xingyuan Wang, Hongkai Zhao, Kexin Bi
This paper proposes a green finance index that may help policymakers and investors take more favorable actions based on the development of green finance. After analysis and organization of the development process of green finance and related green finance and index concepts, this paper uses the improved fuzzy comprehensive evaluation method to construct a measurement model suitable for measuring the
-
The role of odds ratios in joint species distribution modeling Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-02-09 Alan E. Gelfand, Shinichiro Shirota
Joint species distribution modeling is attracting increasing attention these days, acknowledging the fact that individual level modeling fails to take into account expected dependence/interaction between species. These joint models capture species dependence through an associated correlation matrix arising from a set of latent multivariate normal variables. However, these associations offer limited
-
Determinants of CO 2 emissions: empirical evidence from Egypt Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-02-05 Tomiwa Sunday Adebayo, Demet Beton Kalmaz
This paper aims to explore the main determinants of environmental quality in Egypt by utilizing the data covering the years from 1971 to 2014. These dynamics were explored by utilizing the ARDL, wavelet coherence and Gradual shift causality approaches. The ARDL bounds test revealed cointegration among series. Findings based on the ARDL revealed; (i) positive and significant interaction between energy
-
The relationships between ecological urbanization, green areas, and air pollution in Erzurum/Turkey Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-31 Sevgi Yilmaz, Işık Sezen, Elif Nur Sari
The aim of this research is to determine the design criteria of habitable spaces with microclimate data for ecological urbanization. Different types of housing in the city of Erzurum, which is in the northeast region of Turkey, were used in this study. The hourly microclimate and air pollution data from 2018 for the city center were used to analyze the relationships between different residential textures
-
Revisiting the impacts of economic growth on environmental degradation: new evidence from 115 countries Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-30 Mirza Md Moyen Uddin
This paper examines the causal relationship between economic growth and environmental degradation for 115 countries over the period 1990–2016. The empirical results show a long-run equilibrium relationship between the CO2, CH4 and PM2.5 emissions and their macroeconomic determinants economic growth, energy consumption, trade openness, urbanization, and transportation. The author found mixed support
-
Concurrent functional regression to reconstruct river stage data during flood events Environ. Ecol. Stat. (IF 0.981) Pub Date : 2021-01-28 Ryan D. Pittman, David B. Hitchcock, John M. Grego
On October 4, 2015, the Cedar Creek gage at Congaree National Park stopped reporting stages, and the readings did not resume until approximately 2 weeks later because of record-breaking rainfall that led to some of the worst floodings in South Carolina history. Our goal is to reconstruct the Cedar Creek stage during this missing 2-week window. Our analysis uses a sample of ten historical flood events
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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.
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
Contents have been reproduced by permission of the publishers.