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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Review of Economics and Statistics     Hybrid Journal   (Followers: 150)
Statistics in Medicine     Hybrid Journal   (Followers: 139)
Journal of Econometrics     Hybrid Journal   (Followers: 83)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 72, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Biometrics     Hybrid Journal   (Followers: 50)
Sociological Methods & Research     Hybrid Journal   (Followers: 43)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 41)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 40, SJR: 3.664, CiteScore: 2)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 33)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 33)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 28)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 26)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 24)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 23)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
Journal of Forecasting     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 17)
Journal of Statistical Software     Open Access   (Followers: 16, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Computational Statistics     Hybrid Journal   (Followers: 15)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 15)
Demographic Research     Open Access   (Followers: 14)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
International Statistical Review     Hybrid Journal   (Followers: 12)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 11)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 11)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Biometrical Journal     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Current Research in Biostatistics     Open Access   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 8)
Stata Journal     Full-text available via subscription   (Followers: 8)
Lifetime Data Analysis     Hybrid Journal   (Followers: 7)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Significance     Hybrid Journal   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 7)
Journal of Global Optimization     Hybrid Journal   (Followers: 6)
Law, Probability and Risk     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
Statistical Papers     Hybrid Journal   (Followers: 4)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
Building Simulation     Hybrid Journal   (Followers: 2)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Stochastic Models     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
TEST     Hybrid Journal   (Followers: 2)
International Journal of Stochastic Analysis     Open Access   (Followers: 2)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistics and Economics     Open Access  
Review of Socionetwork Strategies     Hybrid Journal  
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
Journal of the Korean Statistical Society     Hybrid Journal  
Sequential Analysis: Design Methods and Applications     Hybrid Journal  

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Similar Journals
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Environmental and Ecological Statistics
Journal Prestige (SJR): 0.594
Citation Impact (citeScore): 1
Number of Followers: 7  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-3009 - ISSN (Online) 1352-8505
Published by Springer-Verlag Homepage  [2469 journals]
  • Exploring land use determinants in Italian municipalities: comparison of
           spatial econometric models

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      Abstract: Abstract This study sets up a spatial econometric framework to explore the factors that best describe land consumption in Italy at the municipal level. By modelling the different types of spatial interactions and geographical proximity between all Italian municipalities, the direct effects of land use drivers are assessed together with spillover effects. Land use data are drawn from the ISPRA-SNPA 82/18 Report and cover all 7,998 Italian municipalities. The results highlight the existence of endogenous and exogenous interaction effects and the crucial role of the demographic, socio-economic and institutional structure on land use intensity. Hence the need for a planning policy aimed at: i) strengthening institutional cooperation to deal with excessive administrative fragmentation; ii) improving institutional and governmental quality to trigger virtuous mechanisms for sustainable land use management.
      PubDate: 2022-07-17
       
  • Evaluation of ecological security for the Association of Southeast Asian
           Nations-5 countries: new evidence from the RALS unit root test

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      Abstract: Abstract The present study seeks to determine the convergence of the ecological footprint pressure index for the Association of Southeast Asian Nations (ASEAN-5) countries over the period of 1961–2017. For this purpose, traditional unit root tests in conjunction with residual augmented least squares (RALS) type unit root tests have been applied to examine the convergence of all countries under investigation. RALS type tests were chosen due to showing a significantly improved power over conventional tests that do not use information on non-normal errors. The traditional unit root results do not show support for the ecological footprint pressure index convergence of the highlighted ASEAN-5 blocs. However, the RALS type and nonlinear unit root tests results reveal that the ecological footprint pressure index became convergent. Thus, governments and policymakers need to adopt stricter policies to protect the environment. These results have a more far-reaching effect on energy and environmental security for the study region.
      PubDate: 2022-07-14
       
  • Distribution-free changepoint detection tests based on the breaking of
           records

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      Abstract: Abstract The analysis of record-breaking events is of interest in fields such as climatology, hydrology or anthropology. In connection with the record occurrence, we propose three distribution-free statistics for the changepoint detection problem. They are CUSUM-type statistics based on the upper and/or lower record indicators observed in a series. Using a version of the functional central limit theorem, we show that the CUSUM-type statistics are asymptotically Kolmogorov distributed. The main results under the null hypothesis are based on series of independent and identically distributed random variables, but a statistic to deal with series with seasonal component and serial correlation is also proposed. A Monte Carlo study of size, power and changepoint estimate has been performed. Finally, the methods are illustrated by analyzing the time series of temperatures at Madrid, Spain. The R package RecordTest publicly available on CRAN implements the proposed methods.
      PubDate: 2022-07-06
       
  • Extending null scenarios with Faddy distributions in a probabilistic
           randomization protocol for presence-absence data

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      Abstract: Abstract Navarro and Manly (Popul Ecol 51:505–512, 2009) (NM) have proposed a randomization protocol for null model analysis of species occurrences at discrete locations based on probability distributions and generalized linear models. In the NM method, presences-absences are governed by independent Bernoulli random variables. In addition, a non-observable non-negative random variable (“quasi-abundance”) from either Poisson, Binomial or Negative Binomial distributions are log-linearly related to the qualitative effects of species and location. By connecting the probability of occurrence of each species on each location and the quasi-abundance distributions, one generalized linear model for the observed presences-absences is selected by profile deviance, and the resulting fitted probabilities of the null model with minimum deviance is used to generate random matrices via parametric bootstrap. This work contributes with a unified theoretical formulation of the NM method, based on Faddy distributions, to allow general distributions of over-dispersed and under-dispersed discrete random variables. For a subset of the Faddy models, the log concave property of the inverse link function guarantees convergence to a global minimum deviance thus providing unique estimates for the linear parameters of the models. The method is illustrated using presence-absence data of island lizard communities. Interpretations of this combined GLM-parametric bootstrap protocol are discussed, highlighting the way fitted probabilities under the chosen null model are related to the row and column totals of the observed table. Additional properties of the probabilistic NM protocol, with possible avenues of future research, are also discussed.
      PubDate: 2022-07-06
       
  • Switching state-space models for modeling penguin population dynamics

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      Abstract: Abstract Tracking individual animals through time using mark-recapture methods is the gold standard for understanding how environmental conditions influence demographic rates, but applying such tags is often infeasible due to the difficulty of catching animals or attaching marks/tags without influencing behavior or survival. Due to the logistical challenges and emerging ethical concerns with flipper banding penguins, relatively little is known about spatial variation in demographic rates, spatial variation in demographic stochasticity, or the role that stochasticity may play in penguin population dynamics. Here we describe how adaptive importance sampling can be used to fit age-structured population models to time series of point counts. While some demographic parameters are difficult to learn through point counts alone, others can be estimated, even in the face of missing data. Here we demonstrate the application of adaptive importance sampling using two case studies, one in which we permit immigration and another permitting regime switching in reproductive success. We apply these methods to extract demographic information from several time series of observed abundance in gentoo and Adélie penguins in Antarctica. Our method is broadly applicable to time series of abundance and provides a feasible means of fitting age-structured models without marking individuals.
      PubDate: 2022-06-21
       
  • Spatio-temporal analysis of air pollution in North China Plain

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      Abstract: Abstract Accompanying China’s rapid industrialization, a vast area of the country, particularly the Beijing–Tianjin–Hebei (BTH) region, has significantly experienced concerning levels of air pollution over the past decade. Exposure to severe particulate matter (PM), \(PM_{2.5}\) in particular, it raises a crucial public health concern, but quantifying \(PM_{2.5}\) accurately across large geographic areas and across time poses a great challenge. To investigate \(PM_{2.5}\) concentration in the BTH region, we utilize a spatio-temporal mixed effects model that includes geographic information system-based time-invariant spatial variables and time-varying meteorological covariates. Our kriging results find that \(PM_{2.5}\) concentration is hazardous in the North China Plain (NCP), where major iron, steel, and cement industries are located. More importantly, our analysis of the impact of wind finds that the severity of air pollution highly depends on the direction of the wind. That is, a northerly wind can considerably reduce the level of \(PM_{2.5}\) in the NCP, while a southerly wind generally does not alleviate air pollution and sometimes even increases it. Using prediction error as a proxy for the level of local emissions, we find that Shijiazhuang and Tangshan produce the most significant local emissions, which coincides with a heavier industry in these two cities. During the winter heating period, we find that the two densely populated cities of Beijing and Tianjin have dramatic increases in local emissions because of the massive coal consumption during this period.
      PubDate: 2022-06-01
      DOI: 10.1007/s10651-021-00521-4
       
  • Tests for aggregated dispersion: Van Valen’s test and a new
           competitor

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      Abstract: Abstract Van Valen’s test is usually applied as a two sample test for equality of dispersion for multivariate data. Motivated by a comment of Manly (Van Valen’s test. Encyclopedia of Statistical Sciences, 2006) that “Little is known about the properties of Van Valen’s test” we develop an alternative test and compare the Van Valen test with our alternative robust test in an extensive simulation study. We find that Van Valen’s test does not actually test for equality of variance sums; however, for that null hypothesis it still performs well in terms of closeness to the nominal significance level. Due to testing the correct null hypothesis and the excellent adherence to the nominal significance level, we recommend the use of the robust test as a permutation test.
      PubDate: 2022-06-01
      DOI: 10.1007/s10651-021-00517-0
       
  • Is globalisation linked to CO2 emission' Evidence from OECD nations

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      Abstract: Abstract An extensive number of studies uses trade-to-GDP as a proxy for globalisation in environmental research. Globalisation encompasses much more than just trade in goods. Globalisation is the integration of various countries and includes spillovers of ideas and technology, financial flows, the worldwide movement of labour, and national governments meeting on an international level in a bid to solve social and political problems. This study considers the effect of globalisation on carbon dioxide emissions by using a more flexible and comprehensive measure based on the KOF globalisation index for a panel of 21 OECD nations covering the period 1970–2014. Since the globalisation process is not uniform across countries and time, we use a fully-fledged nonparametric technique to estimate the time-varying coefficient and trend functions. Our results show that the effect of globalization on CO2 emissions is positive up until 2000, then switches to turns negative thereafter.
      PubDate: 2022-06-01
      DOI: 10.1007/s10651-021-00520-5
       
  • New methods of life expectancy estimation

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      Abstract: Abstract Two novel methods of life expectancy estimation, applied to various annual reported demographic datasets, are proposed. First, for datasets that fully recorded birth date and death date of all dead individuals, we rely on the well-known Kaplan–Meier estimation method to provide an accurate estimation framework of life expectancy. Our proposed method can be used as a gold standard in the accuracy investigation of other life expectancy estimation methods. The method can be applied for small areas, where complete mortality data are regularly produced by routine annual surveys. The second new created method, called as local parametric method, based on the theoretical background of survival process with local parametric Weibull distributions, estimates life expectancy using abridged survival data. Experiments on real longitudinal datasets show the new method provides very exact life expectancy estimations for 10 among 15 one-year datasets, whilst the method of Chiang often yields overestimations.
      PubDate: 2022-05-13
      DOI: 10.1007/s10651-022-00536-5
       
  • Modeling Dinophysis in Western Andalucía using a autoregressive
           hidden Markov model

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      Abstract: Abstract Dinophysis spp. can produce diarrhetic shellfish toxins (DST) including okadaic acid and dinophysistoxins, and some strains can also produce non-diarrheic pectenotoxins. Although DSTs are of human health concern and have motivated environmental monitoring programs in many locations, these monitoring programs often have temporal data gaps (e.g., days without measurements). This paper presents a model for the historical time-series, on a daily basis, of DST-producing toxigenic Dinophysis in 8 monitored locations in western Andalucía over 2015–2020, incorporating measurements of algae counts and DST levels. We fitted a bivariate hidden Markov Model (HMM) incorporating an autoregressive correlation among the observed DST measurements to account for environmental persistence of DST. We then reconstruct the maximum-likelihood profile of algae presence in the water column at daily intervals using the Viterbi algorithm. Using historical monitoring data from Andalucía, the model estimated that potentially toxigenic Dinophysis algae is present at greater than or equal to 250 cells/L between< 1% and>10% of the year depending on the site and year. The historical time-series reconstruction enabled by this method may facilitate future investigations into temporal dynamics of toxigenic Dinophysis blooms.
      PubDate: 2022-05-04
      DOI: 10.1007/s10651-022-00534-7
       
  • A varying-coefficient regression approach to modeling the effects of wind
           speed on the dispersion of pollutants

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      Abstract: Abstract The real-world monitoring system of air pollution ordinarily collects data about pollutant concentration levels at pollution sources and monitors stations in a high-frequency manner. Inspired atmospheric models, the meteorological conditions could play an important role in building up the data-driven model for dispersing atmospheric pollutants from pollution sources to monitor stations. We propose a varying-coefficient model to analyze how emissions of monitor stations are influenced by pollution sources with changing with the wind speed. To estimate the unknown coefficient curves, we use a spline basis to approximate the functions. The asymptotic properties of the proposed method are studied and show the consistency of the estimator. Inference procedures based on a resampling subject bootstrap is developed to construct the conservative confidence bands. A simulation study is carried out to demonstrate the performance of our method. Illustrated by a real-world dataset of environmental sensors collected in Shenyang, China, the proposed varying-coefficient model reveals that the wind speed changes the dispersion mechanism of atmospheric pollutants between monitor stations and pollution sources.
      PubDate: 2022-04-23
      DOI: 10.1007/s10651-022-00535-6
       
  • Estimating change in annual timber products output using a stratified
           sampling with certainty design

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      Abstract: Abstract A key aspect in understanding patterns in wood demand and harvesting activities is monitoring of timber products output by wood processing facilities. Estimation of change from year-to-year is necessary but is complicated due to shifts in the population as well as changing strata over time. Taking independent samples each year eases complexity, yet suffers from relatively large sampling error in comparison to other designs that take advantage of the covariance arising from correlated samples. In this study, a design intended to maximize the precision of the change estimate by retaining the initial sample to the extent possible was analyzed. Several approaches to estimating the covariance, with the primary challenge being that sometimes only a single sample unit occurred in both samples within a given stratum. Variance underestimation and overestimation were encountered depending on the covariance method. The best outcome was attained using a measure-of-size variable at the population level to approximate the covariance. However, this approach overestimated the variance by 11% in a Monte Carlo simulation. The simulation results suggested a 14% reduction in the standard error of the estimate was attainable from correlated samples relative to independent samples. Due to the challenges introduced for estimating the covariance for changing populations and strata over time, the value of relatively small reductions in sampling error need to be considered in the context of introducing complex and potentially unreliable covariance estimation methods.
      PubDate: 2022-03-23
      DOI: 10.1007/s10651-022-00533-8
       
  • Inference and model determination for temperature-driven non-linear
           ecological models

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      Abstract: Abstract This paper is concerned with a contemporary Bayesian approach to the effect of temperature on developmental rates. We develop statistical methods using recent computational tools to model four commonly used ecological non-linear mathematical curves that describe arthropods’ developmental rates. Such models address the effect of temperature fluctuations on the developmental rate of arthropods. In addition to the widely used Gaussian distributional assumption, we also explore Inverse Gamma-based alternatives, which naturally accommodate adaptive variance fluctuation with temperature. Moreover, to overcome the associated parameter indeterminacy in the case of no development, we suggest the zero-inflated Inverse Gamma model. The ecological models are compared graphically via posterior predictive plots and quantitatively via marginal likelihood estimates and Information criteria. Inference is performed using the Stan software and we investigate the statistical and computational efficiency of its Hamiltonian Monte Carlo and Variational Inference methods. We also explore model uncertainty and employ Bayesian Model Averaging framework for robust estimation of the key ecological parameters.
      PubDate: 2022-03-19
      DOI: 10.1007/s10651-022-00531-w
       
  • Dynamic impacts of energy use, agricultural land expansion, and
           deforestation on CO2 emissions in Malaysia

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      Abstract: Abstract This study empirically investigates the nexus among energy use, agricultural land expansion, deforestation, and carbon dioxide (CO2) emissions in Malaysia. Time series data from 1990 to 2019 were utilized using the bounds testing (ARDL) approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the energy usage coefficient is positive and significant with CO2 emissions, indicating a 1% increase in energy consumption is related to a 0.91% rise in CO2 emissions. In addition, the coefficient of agricultural land is positive, which indicates that agricultural land expansion by 1% is associated with an increase in CO2 emissions by 0.84% in the long run. Furthermore, the forested area coefficient is negative, which means that decreasing 1% of the wooded area (i.e., deforestation) has a long-term effect of 5.41% increased CO2 emissions. Moreover, the pairwise Granger causality test results show bidirectional causality between deforestation and energy use; and unidirectional causality from energy use to CO2 emissions, agricultural land expansion to CO2 emissions, deforestation to CO2 emissions, agricultural land expansion to energy use, and deforestation to agricultural land expansion in Malaysia. The empirical findings reveal that increased energy use, agricultural land expansion, and deforestation have a negative impact on environmental quality in Malaysia. Thus, the effective implementation of policy measures to promote renewable energy, climate-smart agriculture, and sustainable management of forest ecosystems could be useful for reducing environmental degradation in Malaysia.
      PubDate: 2022-03-17
      DOI: 10.1007/s10651-022-00532-9
       
  • Guest Editorial of the SEEM-2019 conference EEST special issue

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      PubDate: 2022-02-15
      DOI: 10.1007/s10651-022-00530-x
       
  • Estimating wild boar density in hunting areas by a probabilistic sampling
           of drive counts

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      Abstract: Abstract The evaluation of wild boar density in a hunting district can be performed by accurate drive counts of boars within the drive areas assigned to each hunting team. Because a complete driving of all the areas is prohibitive, only a subset is driven in a hunting occasion. Results are highly dependent on the subjective choice of these areas. In this study, an objective design-based approach is considered in which areas to be driven are randomly selected one per team in accordance with the one-per-stratum sampling scheme. Because the areas assigned to hunting teams are likely to be close to each other, the one-per-stratum sampling is likely to achieve samples of evenly spread areas. Then, the subsequent step is to choose the selection criterion for the areas and the estimation criterion for exploiting or not the information provided by area sizes. To this purpose, three sampling strategies are considered, together with methods to estimate their precision. These strategies are checked and compared by means of a simulation study performed on artificial populations constructed from the list of drive areas settled in the Province of Massa–Carrara (Italy) and partitioned among 39 hunting teams. Results from artificial populations give clear insights about the most suitable strategy to be used. Drive counts performed in this province in two hunting occasions during 2019 within 39 areas selected by one-per-stratum sampling are adopted as case studies.
      PubDate: 2022-01-18
      DOI: 10.1007/s10651-021-00527-y
       
  • How should surface elevation table data be analyzed' A comparison of
           several commonly used analysis methods and one newly proposed approach

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      Abstract: Abstract The use of surface elevation table (SET) instruments to monitor elevation changes at low elevation coastal locations has steadily increased in recent years. A primary focus in the analysis of SET data is the estimation of the overall rate of elevation change, and numerous approaches have been used for this purpose. In this work, we compare and contrast several methods used for estimating the true rate of elevation change at SET station locations, including a novel approach proposed in this work that incorporates spatial dependence. We also discuss theoretical properties of one class of estimators, and undertake a comprehensive simulation study. Additionally, we present two case studies where we illustrate these differences using real SET data. All methods considered here tend to produce similar point estimates, but some confidence interval procedures can generate intervals with empirical coverage rates lower than specified. However, the best analysis approach is likely dependent upon selecting the method that best coincides with the true underlying process. Thus, we do not uniformly recommend one approach for all situations. Instead, we suggest carefully weighing potential advantages and disadvantages of each method before conducting analysis, while keeping in mind the ways in which modeling assumptions may impact this decision.
      PubDate: 2022-01-09
      DOI: 10.1007/s10651-021-00524-1
       
  • Revisiting the carbon emissions hypothesis in the developing and developed
           countries: a new panel cointegration approach

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      Abstract: Abstract Since global warming worsens with economic development and emitted CO2 is one of the main greenhouse gases, it is important to understand the relationship between CO2 emissions and economic growth. The paper applies a new panel cointegration test with cross-sectional dependence and structural breaks to examine this relationship in developed and developing countries, respectively. The results indicate that the “Environmental Kuznets Curve” does not hold in either group. For developing countries, there is neither linear nor quadratic long-term equilibrium relationship between CO2 emissions and economic growth. For developed countries, the quadratic relationship does exist between CO2 emissions and economic growth, whereas the linear one does not. A half of these countries have inverted U-shaped curves, while the other half have U-shaped curves. Besides, most of these countries are still on the rising stage of the curve. This paper gives new insights for policymakers to keep a balance between sustainable economic growth and suitable environmental quality.
      PubDate: 2022-01-04
      DOI: 10.1007/s10651-021-00526-z
       
  • Modelling multivariate data using product copulas and minimum distance
           estimators: an exemplary application to ecological traits

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      Abstract: Abstract Modelling and applying multivariate distributions is an important topic in ecology. In particular in plant ecology, the multidimensional nature of plant traits comes with challenges such as wide ranges in observations as well as correlations between several characteristics. In other disciplines (e.g., finances and economics), copulas have been proven as a valuable tool for modelling multivariate distributions. However, applications in ecology are still rarely used. Here, we present a copula-based methodology of fitting multivariate distributions to ecological data. We used product copula models to fit multidimensional plant traits, on example of observations from the global trait database TRY. The fitting procedure is split into two parts: fitting the marginal distributions and fitting the copula. We found that product copulas are well suited to model ecological data as they have the advantage of being asymmetric (similar to the observed data). Challenges in the fitting were mainly addressed to limited amount of data. In view of growing global databases, we conclude that copula modelling provides a great potential for ecological modelling.
      PubDate: 2022-01-04
      DOI: 10.1007/s10651-021-00525-0
       
  • Study on changes of urban spatial pattern and heterogeneity of driving
           factors in the Su-Xi-Chang region

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      Abstract: Abstract Using the Suzhou-Wuxi-Changzhou (referred to as Su-Xi-Chang) region as a case study, this work applied an Exploratory Spatial Data Analysis model to study the characteristics associated with the evolution in the urban spatial patterns in the region from 2002 to 2018. A geographical weighted regression model and Local indicator of spatial association Index are used to analyze the degrees of influence that different driving factors have on urban spatial patterns in the Su-Xi-Chang region. Two major points emerged from the results. First, the urban development of the Su-Xi-Chang metropolitan area has a relatively concentrated spatial distribution. When considering the local spatial correlation, there is a relatively large proportion of areas with H–H correlation and L–H correlation. The H–H correlation area is mainly concentrated in the central urban area of Suzhou and Wuxi, and Kunshan, which connects Suzhou and Shanghai. This forms a spatial concentration area with high urban development levels. The L–H correlation area is mainly concentrated in cities such as Yixing and Changshu. After the central city developed to a certain stage in 2010, the spatial agglomeration of small and medium-sized cities that lagged in size became more clear. The L–L agglomeration area is mainly concentrated in Liyang and Jintan, with a widening development gap from surrounding cities and counties. This has led to a development trend of marginalization. Second, the urbanization rate index had a weak driving effect on the evolution and development of urban spatial pattern.
      PubDate: 2022-01-04
      DOI: 10.1007/s10651-021-00523-2
       
 
JournalTOCs
School of Mathematical and Computer Sciences
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