cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1080737.v9
title: Legislative correlates of the biophysical attributes of Canadian protected areas

description: This data file contains the R code and data that are used in the manuscript Leroux et al. (in revision). Legislative correlates of the size of protected areas in Canada. Conservation Biology. The data file includes information on Canadian protected areas. Specifically, it includes the name, area, IUCN category, jurisdiction, time of establishment, ecozone, governing legislation and whether it includes provisions for scientific knowledge, operating and/or capital cost recovery and stakeholder involvement in planning and management.
DOI: 10.6084/m9.figshare.1068626.v1
title: Nutrient accumulation in aboveground biomass of planted tropical trees: a meta-analysis

description: Efficient nutrient use is essential for biomass production by tropical trees growing in infertile soils. Accumulation of nitrogen (N) and phosphorus (P) in the aboveground biomass of four groups of tree stands [<i>Acacia</i>, <i>Eucalyptus</i>, N<sub>2</sub>-fixing trees excluding <i>Acacia</i>, and other non-N<sub>2</sub>-fixing broadleaved (ONNFB) trees] were investigated using meta-analyses of a range of biomass data to test the hypothesis that fast-growing <i>Acacia</i> and <i>Eucalyptus</i> trees accumulate fewer nutrients. Data for 83 tropical tree stands were selected from the literature. Standardized major axis regressions were applied between the log<sub>10</sub>-transformed biomass and N or P accumulation. Nutrient use efficiency was compared with aboveground biomass and topsoil conditions. The slope of the regression between aboveground biomass and N accumulation for <i>Eucalyptus</i> was significantly smaller than the slopes for the N<sub>2</sub>-fixing trees (excluding <i>Acacia</i>) and the ONNFB trees. N use efficiency of <i>Eucalyptus</i> increased with biomass more than that of N<sub>2</sub>-fixing trees (excluding <i>Acacia</i>) and the ONNFB trees, because their stems and twigs tended to accumulate less N than in the other groups as biomass increased. The regressions between aboveground biomass and P accumulation had a common slope, and the intercepts of <i>Acacia</i> and <i>Eucalyptus</i> were significantly lower than that of ONNFB trees. P use efficiency of <i>Acacia</i> was consistently higher than that of the ONNFB trees. P use efficiency is more affected by other factors like soil conditions than is N use efficiency, and the differences in the tree groups significantly affect the use efficiency of both nutrients. These results explained some aspects of the general suitability of <i>Acacia</i> and <i>Eucalyptus</i> species for tropical plantations on infertile soils.
DOI: 10.6084/m9.figshare.1080737.v10
title: Legislative correlates of the biophysical attributes of Canadian protected areas

description: This data file contains the R code and data that are used in the manuscript Leroux et al. (submitted). Legislative correlates of the size of protected areas in Canada. The data file includes information on Canadian protected areas. Specifically, it includes the name, area, IUCN category, jurisdiction, time of establishment, ecozone, governing legislation and whether it includes provisions for scientific knowledge, operating and/or capital cost recovery and stakeholder involvement in planning and management.
DOI: 10.6084/m9.figshare.1080737.v11
title: Legislative correlates of the biophysical attributes of Canadian protected areas

description: This data file contains the R code and data that are used in the manuscript Leroux et al. (submitted). Legislative correlates of the size of protected areas in Canada. The data file includes information on Canadian protected areas. Specifically, it includes the name, area, IUCN category, jurisdiction, time of establishment, ecozone, governing legislation and whether it includes provisions for scientific knowledge, operating and/or capital cost recovery and stakeholder involvement in planning and management.
DOI: 10.6084/m9.figshare.1067966
title: Rohdaten VHN

description: Rohdaten "Vierteljahresschrift für Heilpädagogik und ihre Nachbargebiete"
DOI: 10.6084/m9.figshare.1067968
title: Rohdaten ZfH

description: Rohdaten "Zeitschrift für Heilpädagogik"
DOI: 10.6084/m9.figshare.1067965
title: Rohdaten UW

description: Rohdaten "Unterrichtswissenschaft"
DOI: 10.6084/m9.figshare.1067968.v1
title: Rohdaten ZfH

description: Rohdaten "Zeitschrift für Heilpädagogik"
DOI: 10.6084/m9.figshare.1080737.v12
title: Legislative correlates of the size and number of protected areas in Canadian jurisdictions

description: This data file contains the R code and data that are used in the manuscript Leroux et al. (submitted). Legislative correlates of the size of protected areas in Canada. The data file includes information on Canadian protected areas. Specifically, it includes the name, area, IUCN category, jurisdiction, time of establishment, ecozone, governing legislation and whether it includes provisions for scientific knowledge, operating and/or capital cost recovery and stakeholder involvement in planning and management.
DOI: 10.6084/m9.figshare.1067962
title: Rohdaten PEU

description: Rohdaten "Psychologie in Erziehung und Unterricht"
DOI: 10.6084/m9.figshare.1067965.v1
title: Rohdaten UW

description: Rohdaten "Unterrichtswissenschaft"
DOI: 10.6084/m9.figshare.1067966.v1
title: Rohdaten VHN

description: Rohdaten "Vierteljahresschrift für Heilpädagogik und ihre Nachbargebiete"
DOI: 10.6084/m9.figshare.1067962.v1
title: Rohdaten PEU

description: Rohdaten "Psychologie in Erziehung und Unterricht"
DOI: 10.6084/m9.figshare.1067958
title: Rohdaten EP

description: Rohdaten "Empirische Pädagogik"
DOI: 10.6084/m9.figshare.1067959
title: Rohdaten ESP

description: Rohdaten "Empirische Sonderpädagogik"
DOI: 10.6084/m9.figshare.1067960
title: Rohdaten HeiFo

description: Rohdaten "Heilpädagogische Forschung"
DOI: 10.6084/m9.figshare.1067958.v1
title: Rohdaten EP

description: Rohdaten "Empirische Pädagogik"
DOI: 10.6084/m9.figshare.1067959.v1
title: Rohdaten ESP

description: Rohdaten "Empirische Sonderpädagogik"
DOI: 10.6084/m9.figshare.1067960.v1
title: Rohdaten HeiFo

description: Rohdaten "Heilpädagogische Forschung"
DOI: 10.6084/m9.figshare.1067080
title: Yirrabana Collaboration

description: Yirrabana this way | collaboration The Yirrabana process describes how Paramodic interacts with communities to enable meaningful involvement of community with other partners, for mutual benefit. It describes the seven stages of interaction, beginning and ending with Nura. It is a living, evolving resource and an integral part of the Paramodic Data Management Plan.
DOI: 10.6084/m9.figshare.1067913
title: INFORMATION NEEDS ON RURAL WOMEN: A STUDY OF TAMIL NADU, INDIA

description: The present age has been rightly called as an Information Age. Information has become the most important element<br>for progress in society. According to Kemp “information has been described as the fifth need of man ranking after air, water,<br>food and shelter”. Everyone needs information about everything even in his day to day life.
DOI: 10.6084/m9.figshare.1067080.v1
title: Yirrabana Collaboration

description: Yirrabana this way | collaboration The Yirrabana process describes how Paramodic interacts with communities to enable meaningful involvement of community with other partners, for mutual benefit. It describes the seven stages of interaction, beginning and ending with Nura. It is a living, evolving resource and an integral part of the Paramodic Data Management Plan.
DOI: 10.6084/m9.figshare.1067057
title: Smoothing Windows for the Synthesis of Gaussian Stationary Random Fields Using Circulant Matrix Embedding

description: When generating Gaussian stationary random fields, a standard method based on circulant matrix embedding usually fails because some of the associated eigenvalues are negative. The eigenvalues can be shown to be nonnegative in the limit of increasing sample size. Computationally feasible large sample sizes, however, rarely lead to nonnegative eigenvalues. Another solution is to extend suitably the covariance function of interest so that the eigenvalues of the embedded circulant matrix become nonnegative in theory. Though such extensions have been found for a number of examples of stationary fields, the method depends on nontrivial constructions in specific cases.In this work, the embedded circulant matrix is smoothed at the boundary by using a cutoff window or overlapping windows over a transition region. The windows are not specific to particular examples of stationary fields. The resulting method modifies the standard circulant embedding, and is easy to use. It is shown that this straightforward approach works for many examples of interest, with the overlapping windows performing consistently better. The method even outperforms in the cases where extending the covariance leads to nonnegative eigenvalues in theory, in the sense that the transition region is considerably smaller. The Matlab code implementing the method is included in the online supplementary materials and also publicly available at www.hermir.org.
DOI: 10.6084/m9.figshare.1067068
title: Ryan et al. 2014 - Sex Ratio Data

description: This data is used in Ryan et al. 2014. It examines sex ratio, litter size, testosterone, fecal glucocorticoid metabolites, plasma cortisol in bound, free and total fractions, and glucose in free-living ground squirrels <em>(Urocitellus richardsonii)</em>.<br>Edited 2020/02/24 to include metadata for dataset. <br>
DOI: 10.6084/m9.figshare.1067054
title: The Open-Faced Sandwich Adjustment for MCMC Using Estimating Functions

description: A situation frequently arises where working with the likelihood function is problematic. This can happen for several reasons—perhaps the likelihood is prohibitively computationally expensive, perhaps it lacks some robustness property, or perhaps it is simply not known for the model under consideration. In these cases, it is often possible to specify alternative functions of the parameters and the data that can be maximized to obtain asymptotically normal estimates. However, these scenarios present obvious problems if one is interested in applying Bayesian techniques. This article describes open-faced sandwich adjustment, a way to incorporate a wide class of nonlikelihood objective functions within Bayesian-like models to obtain asymptotically valid parameter estimates and inference via MCMC. Two simulation examples show that the method provides accurate frequentist uncertainty estimates. The open-faced sandwich adjustment is applied to a Poisson spatio-temporal model to analyze an ornithology dataset from the citizen science initiative eBird. An online supplement contains an appendix with additional figures, tables, and discussion, as well as R code.
DOI: 10.6084/m9.figshare.1067057.v2
title: Smoothing Windows for the Synthesis of Gaussian Stationary Random Fields Using Circulant Matrix Embedding

description: When generating Gaussian stationary random fields, a standard method based on circulant matrix embedding usually fails because some of the associated eigenvalues are negative. The eigenvalues can be shown to be nonnegative in the limit of increasing sample size. Computationally feasible large sample sizes, however, rarely lead to nonnegative eigenvalues. Another solution is to extend suitably the covariance function of interest so that the eigenvalues of the embedded circulant matrix become nonnegative in theory. Though such extensions have been found for a number of examples of stationary fields, the method depends on nontrivial constructions in specific cases.In this work, the embedded circulant matrix is smoothed at the boundary by using a cutoff window or overlapping windows over a transition region. The windows are not specific to particular examples of stationary fields. The resulting method modifies the standard circulant embedding, and is easy to use. It is shown that this straightforward approach works for many examples of interest, with the overlapping windows performing consistently better. The method even outperforms in the cases where extending the covariance leads to nonnegative eigenvalues in theory, in the sense that the transition region is considerably smaller. The Matlab code implementing the method is included in the online supplementary materials and also publicly available at www.hermir.org.
DOI: 10.6084/m9.figshare.1067054.v2
title: The Open-Faced Sandwich Adjustment for MCMC Using Estimating Functions

description: A situation frequently arises where working with the likelihood function is problematic. This can happen for several reasons—perhaps the likelihood is prohibitively computationally expensive, perhaps it lacks some robustness property, or perhaps it is simply not known for the model under consideration. In these cases, it is often possible to specify alternative functions of the parameters and the data that can be maximized to obtain asymptotically normal estimates. However, these scenarios present obvious problems if one is interested in applying Bayesian techniques. This article describes open-faced sandwich adjustment, a way to incorporate a wide class of nonlikelihood objective functions within Bayesian-like models to obtain asymptotically valid parameter estimates and inference via MCMC. Two simulation examples show that the method provides accurate frequentist uncertainty estimates. The open-faced sandwich adjustment is applied to a Poisson spatio-temporal model to analyze an ornithology dataset from the citizen science initiative eBird. An online supplement contains an appendix with additional figures, tables, and discussion, as well as R code.
DOI: 10.6084/m9.figshare.1067057.v1
title: Smoothing Windows for the Synthesis of Gaussian Stationary Random Fields Using Circulant Matrix Embedding

description: When generating Gaussian stationary random fields, a standard method based on circulant matrix embedding usually fails because some of the associated eigenvalues are negative. The eigenvalues can be shown to be nonnegative in the limit of increasing sample size. Computationally feasible large sample sizes, however, rarely lead to nonnegative eigenvalues. Another solution is to extend suitably the covariance function of interest so that the eigenvalues of the embedded circulant matrix become nonnegative in theory. Though such extensions have been found for a number of examples of stationary fields, the method depends on nontrivial constructions in specific cases.In this work, the embedded circulant matrix is smoothed at the boundary by using a cutoff window or overlapping windows over a transition region. The windows are not specific to particular examples of stationary fields. The resulting method modifies the standard circulant embedding, and is easy to use. It is shown that this straightforward approach works for many examples of interest, with the overlapping windows performing consistently better. The method even outperforms in the cases where extending the covariance leads to nonnegative eigenvalues in theory, in the sense that the transition region is considerably smaller. The Matlab code implementing the method is included in the online supplementary materials and also publicly available at www.hermir.org.
DOI: 10.6084/m9.figshare.1067053
title: Variable Selection Diagnostics Measures for High-Dimensional Regression

description: Many exciting results have been obtained on model selection for high-dimensional data in both efficient algorithms and theoretical developments. The powerful penalized regression methods can give sparse representations of the data even when the number of predictors is much larger than the sample size. One important question then is: How do we know when a sparse pattern identified by such a method is reliable? In this work, besides investigating instability of model selection methods in terms of variable selection, we propose variable selection deviation measures that give one a proper sense on how many predictors in the selected set are likely trustworthy in certain aspects. Simulation and a real data example demonstrate the utility of these measures for application.
DOI: 10.6084/m9.figshare.1067054.v1
title: The Open-Faced Sandwich Adjustment for MCMC Using Estimating Functions

description: A situation frequently arises where working with the likelihood function is problematic. This can happen for several reasons—perhaps the likelihood is prohibitively computationally expensive, perhaps it lacks some robustness property, or perhaps it is simply not known for the model under consideration. In these cases, it is often possible to specify alternative functions of the parameters and the data that can be maximized to obtain asymptotically normal estimates. However, these scenarios present obvious problems if one is interested in applying Bayesian techniques. This article describes open-faced sandwich adjustment, a way to incorporate a wide class of nonlikelihood objective functions within Bayesian-like models to obtain asymptotically valid parameter estimates and inference via MCMC. Two simulation examples show that the method provides accurate frequentist uncertainty estimates. The open-faced sandwich adjustment is applied to a Poisson spatio-temporal model to analyze an ornithology dataset from the citizen science initiative eBird. An online supplement contains an appendix with additional figures, tables, and discussion, as well as R code.
DOI: 10.6084/m9.figshare.1067050
title: Adaptive Bayesian Nonstationary Modeling for Large Spatial Datasets Using Covariance Approximations

description: Gaussian process models have been widely used in spatial statistics but face tremendous modeling and computational challenges for very large nonstationary spatial datasets. To address these challenges, we develop a Bayesian modeling approach using a nonstationary covariance function constructed based on adaptively selected partitions. The partitioned nonstationary class allows one to knit together local covariance parameters into a valid global nonstationary covariance for prediction, where the local covariance parameters are allowed to be estimated within each partition to reduce computational cost. To further facilitate the computations in local covariance estimation and global prediction, we use the full-scale covariance approximation (FSA) approach for the Bayesian inference of our model. One of our contributions is to model the partitions stochastically by embedding a modified treed partitioning process into the hierarchical models that leads to automated partitioning and substantial computational benefits. We illustrate the utility of our method with simulation studies and the global Total Ozone Matrix Spectrometer (TOMS) data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1067051
title: Tree-Structured Mixed-Effects Regression Modeling for Longitudinal Data

description: Tree-structured models have been widely used because they function as interpretable prediction models that offer easy data visualization. A number of tree algorithms have been developed for univariate response data and can be extended to analyze multivariate response data. We propose a tree algorithm by combining the merits of a tree-based model and a mixed-effects model for longitudinal data. We alleviate variable selection bias through residual analysis, which is used to solve problems that exhaustive search approaches suffer from, such as undue preference to split variables with more possible splits, expensive computational cost, and end-cut preference. Most importantly, our tree algorithm discovers trends over time on each of the subspaces from recursive partitioning, while other tree algorithms predict responses. We investigate the performance of our algorithm with both simulation and real data studies. We also develop an R package melt that can be used conveniently and freely. Additional results are provided as online supplementary material.
DOI: 10.6084/m9.figshare.1067049
title: A Graphical Goodness-of-Fit Test for Dependence Models in Higher Dimensions

description: This article introduces a graphical goodness-of-fit test for copulas in more than two dimensions. The test is based on pairs of variables and can thus be interpreted as a first-order approximation of the underlying dependence structure. The idea is to first transform pairs of data columns with the Rosenblatt transform to bivariate standard uniform distributions under the null hypothesis. This hypothesis can be graphically tested with a matrix of bivariate scatterplots, Q-Q plots, or other transformations. Furthermore, additional information can be encoded as background color, such as measures of association or (approximate) <i>p</i>-values of tests of independence. The proposed goodness-of-fit test is designed as a basic graphical tool for detecting deviations from a postulated, possibly high-dimensional, dependence model. Various examples are given and the methodology is applied to a financial dataset. An implementation is provided by the R package copula. Supplementary material for this article is available online, which provides the R package copula and reproduces all the graphical results of this article.
DOI: 10.6084/m9.figshare.1067052
title: Graphical Aids for the Analysis of Two-Level Nonregular Designs

description: The complex alias pattern between main effects and two-factor interactions for two-level nonregular designs has been considered a problem when analyzing these designs. If only a few two-factor interactions are active, however, the pattern induced into the estimated main effects contrasts from the active interactions may be very structured. This is, in particular, true for the 12-run and the 20-run Plackett–Burman (PB) designs, probably the two most important designs for physical experimentation. This article presents a graphical method for the analysis of nonregular two-level designs. The method consists of two steps. The first step is called contrast plots interpretation and is directed toward revealing the cause for the pattern observed in contrast plots. The second step is called alias reduction and aims at simplifying the interpretation of the contrast plots by reducing the aliasing caused by effects that, with a high degree of certainty, may be considered active. The method is tested on the 12-run PB design both with simulated and real data and on the 20-run PB design for one particular case with real data. Supplementary materials (MINITAB codes for performing calculations and plots) are available online.
DOI: 10.6084/m9.figshare.1067049.v2
title: A Graphical Goodness-of-Fit Test for Dependence Models in Higher Dimensions

description: This article introduces a graphical goodness-of-fit test for copulas in more than two dimensions. The test is based on pairs of variables and can thus be interpreted as a first-order approximation of the underlying dependence structure. The idea is to first transform pairs of data columns with the Rosenblatt transform to bivariate standard uniform distributions under the null hypothesis. This hypothesis can be graphically tested with a matrix of bivariate scatterplots, Q-Q plots, or other transformations. Furthermore, additional information can be encoded as background color, such as measures of association or (approximate) <i>p</i>-values of tests of independence. The proposed goodness-of-fit test is designed as a basic graphical tool for detecting deviations from a postulated, possibly high-dimensional, dependence model. Various examples are given and the methodology is applied to a financial dataset. An implementation is provided by the R package copula. Supplementary material for this article is available online, which provides the R package copula and reproduces all the graphical results of this article.