cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28454482
title: Clustering Spatial Data with a Mixture of Skewed Regression Models

description: A single regression model is unlikely to hold throughout a large and complex spatial domain. A finite mixture of regression models can address this issue by clustering the data and assigning a regression model to explain each homogenous group. However, a typical finite mixture of regressions does not account for spatial dependencies. Furthermore, the number of components selected can be too high in the presence of skewed data and/or heavy tails. Here, we propose a mixture of regression models on a Markov random field with skewed distributions. The proposed model identifies the locations wherein the relationship between the predictors and the response is similar and estimates the model within each group as well as the number of groups. Overfitting is addressed by using skewed distributions, such as the skew-<i>t</i> or normal inverse Gaussian, in the error term of each regression model. Model estimation is carried out using an EM algorithm, and the performance of the estimators and model selection are illustrated through an extensive simulation study and two case studies.
DOI: 10.6084/m9.figshare.28454482.v1
title: Clustering Spatial Data with a Mixture of Skewed Regression Models

description: A single regression model is unlikely to hold throughout a large and complex spatial domain. A finite mixture of regression models can address this issue by clustering the data and assigning a regression model to explain each homogenous group. However, a typical finite mixture of regressions does not account for spatial dependencies. Furthermore, the number of components selected can be too high in the presence of skewed data and/or heavy tails. Here, we propose a mixture of regression models on a Markov random field with skewed distributions. The proposed model identifies the locations wherein the relationship between the predictors and the response is similar and estimates the model within each group as well as the number of groups. Overfitting is addressed by using skewed distributions, such as the skew-<i>t</i> or normal inverse Gaussian, in the error term of each regression model. Model estimation is carried out using an EM algorithm, and the performance of the estimators and model selection are illustrated through an extensive simulation study and two case studies.
DOI: 10.6084/m9.figshare.28582137.v2
title: Robust Covariance Estimation and Explainable Outlier Detection for Matrix-Valued Data

description: This work introduces the Matrix Minimum Covariance Determinant (MMCD) method, a novel robust location and covariance estimation procedure designed for data that are naturally represented in the form of a matrix. Unlike standard robust multivariate estimators, which would only be applicable after a vectorization of the matrix-variate samples leading to high-dimensional datasets, the MMCD estimators account for the matrix-variate data structure and consistently estimate the mean matrix, as well as the rowwise and columnwise covariance matrices in the class of matrix-variate elliptical distributions. Additionally, we show that the MMCD estimators are matrix affine equivariant and achieve a higher breakdown point than the maximal achievable one by any multivariate, affine equivariant location/covariance estimator when applied to the vectorized data. An efficient algorithm with convergence guarantees is proposed and implemented. As a result, robust Mahalanobis distances based on MMCD estimators offer a reliable tool for outlier detection. Additionally, we extend the concept of Shapley values for outlier explanation to the matrix-variate setting, enabling the decomposition of the squared Mahalanobis distances into contributions of the rows, columns, or individual cells of matrix-valued observations. Notably, both the theoretical guarantees and simulations show that the MMCD estimators outperform robust estimators based on vectorized observations, offering better computational efficiency and improved robustness. Moreover, real-world data examples demonstrate the practical relevance of the MMCD estimators and the resulting robust Shapley values.
DOI: 10.6084/m9.figshare.28451772
title: Optimal Planning of Destructive Degradation Tests

description: In many reliability applications, degradation of products has to be measured destructively, and destructive degradation tests are a useful tool to evaluate product reliability. Previous studies commonly obtain an optimal degradation test plan numerically with given planning values of model parameters, under a default assumption that stress acceleration is necessary. In this study, we use the general path model for product degradation and derive closed-form solutions for optimal designs of a destructive degradation test, under the planning objective of minimizing the asymptotic variance of the estimated lifetime quantile. Based on these results, we further identify conditions under which acceleration is necessary or unnecessary. It is found that the key parameters that determine the necessity of acceleration are the lifetime quantile and the parameter associated with the accelerating variable in the link function. We demonstrate the application of the results by applying them to an adhesive bond test and a seal test. Several compromise plans are investigated to robustify the test. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.28574269
title: A Spatially Correlated Competing Risks Time-to-Event Model for Supercomputer GPU Failure Data

description: Graphics processing units (GPUs) are widely used in many high-performance computing (HPC) applications such as imaging/video processing and training deep-learning models in artificial intelligence. GPUs installed in HPC systems are often heavily used, and GPU failures occur during HPC system operations. Thus, the reliability of GPUs is of interest for the overall reliability of HPC systems. The Cray XK7 Titan supercomputer was one of the top ten supercomputers in the world. The failure event times of more than 30,000 GPUs in Titan were recorded and previous data analysis suggested that the failure time of a GPU may be affected by the GPU’s connectivity location inside the supercomputer among other factors. In this article, we conduct in-depth statistical modeling of GPU failure times to study the effect of location on GPU failures under competing risks with covariates and spatially correlated random effects. In particular, two major failure types of GPUs in Titan are considered. The connectivity locations of cabinets are modeled as spatially correlated random effects, and the positions of GPUs inside each cabinet are treated as covariates. A Bayesian framework is used for statistical inference. We also compare different methods of estimation such as the maximum likelihood, which is implemented via an expectation-maximization algorithm. Our results provide interesting insights into GPU failures in HPC systems. This article has online supplementary materials.
DOI: 10.6084/m9.figshare.28574269.v1
title: A Spatially Correlated Competing Risks Time-to-Event Model for Supercomputer GPU Failure Data

description: Graphics processing units (GPUs) are widely used in many high-performance computing (HPC) applications such as imaging/video processing and training deep-learning models in artificial intelligence. GPUs installed in HPC systems are often heavily used, and GPU failures occur during HPC system operations. Thus, the reliability of GPUs is of interest for the overall reliability of HPC systems. The Cray XK7 Titan supercomputer was one of the top ten supercomputers in the world. The failure event times of more than 30,000 GPUs in Titan were recorded and previous data analysis suggested that the failure time of a GPU may be affected by the GPU’s connectivity location inside the supercomputer among other factors. In this article, we conduct in-depth statistical modeling of GPU failure times to study the effect of location on GPU failures under competing risks with covariates and spatially correlated random effects. In particular, two major failure types of GPUs in Titan are considered. The connectivity locations of cabinets are modeled as spatially correlated random effects, and the positions of GPUs inside each cabinet are treated as covariates. A Bayesian framework is used for statistical inference. We also compare different methods of estimation such as the maximum likelihood, which is implemented via an expectation-maximization algorithm. Our results provide interesting insights into GPU failures in HPC systems. This article has online supplementary materials.
DOI: 10.6084/m9.figshare.28582137.v1
title: Robust covariance estimation and explainable outlier detection for matrix-valued data

description: This work introduces the Matrix Minimum Covariance Determinant (MMCD) method, a novel robust location and covariance estimation procedure designed for data that are naturally represented in the form of a matrix. Unlike standard robust multivariate estimators, which would only be applicable after a vectorization of the matrix-variate samples leading to high-dimensional datasets, the MMCD estimators account for the matrix-variate data structure and consistently estimate the mean matrix, as well as the rowwise and columnwise covariance matrices in the class of matrix-variate elliptical distributions. Additionally, we show that the MMCD estimators are matrix affine equivariant and achieve a higher breakdown point than the maximal achievable one by any multivariate, affine equivariant location/covariance estimator when applied to the vectorized data. An efficient algorithm with convergence guarantees is proposed and implemented. As a result, robust Mahalanobis distances based on MMCD estimators offer a reliable tool for outlier detection. Additionally, we extend the concept of Shapley values for outlier explanation to the matrix-variate setting, enabling the decomposition of the squared Mahalanobis distances into contributions of the rows, columns, or individual cells of matrix-valued observations. Notably, both the theoretical guarantees and simulations show that the MMCD estimators outperform robust estimators based on vectorized observations, offering better computational efficiency and improved robustness. Moreover, real-world data examples demonstrate the practical relevance of the MMCD estimators and the resulting robust Shapley values.
DOI: 10.21233/27e6-sb51
title: Kogyae Plot 1 (Forest plot) pollen surface sample dataset

description: Raw data for the Kogyae Plot 1 (Forest plot) pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.57745/hlqfiz
title: Metagenomics.tab

description: :unav
DOI: 10.21233/71rw-fx11
title: Souris River ostracode surface sample dataset

description: Raw data for the Souris River ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.7910/dvn/daakz5
title: Replication Data for: Types of pandemic-induced psychological distress, clarity of responsibility, and support for incumbents

description: Will voters punish incumbents for psychological distress associated with public policy during external shocks? This study examines this question in the empirical context of the first wave of the COVID-19 pandemic in India, utilizing three novel cross-sectional surveys conducted in the first three weeks of June 2020, immediately after the national lockdown policy was officially revoked. We find that propensity to vote for the nationally incumbent Bharatiya Janata Party (if hypothetical elections were held on the day of the survey) was negatively correlated with mental stress from routine disruptions in mobility (Week 1); worsening mental health (Week 2); and emotion-focused coping (Week 3). We show that these effects are strongest in BJP-ruled states. We argue that psychological distress shaped political attitudes in the midst of the pandemic and this effect was conditional on the source of distress and moderated by governmental clarity of responsibility.
DOI: 10.21233/cvkq-5n30
title: Waverveen II (B31B0862) pollen dataset

description: Raw data for the Waverveen II (B31B0862) pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.5281/zenodo.15296686
title: Balancing Act: The Cost of Wind Restrictions in Norway's Electricity Transition
DOI: 10.21233/7c4d-8w92
title: Numrug ostracode surface sample dataset

description: Raw data for the Numrug ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.5281/zenodo.15387693
title: xerosicyos_decaryi_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.15387694
title: xerosicyos_decaryi_zanfona_1.fasta.gz
DOI: 10.21233/4hmj-2b83
title: Eight Point Lake diatom dataset

description: Raw data for the Eight Point Lake diatom dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/ts97-k242
title: Croaghaun East pollen dataset

description: Raw data for the Croaghaun East pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.6084/m9.figshare.29038550
title: Photodissociation Dynamics of XH+ (X = Na, K, Rb, Cs): Rovibrationally Resolved Shape Resonances Driven by Potential Barriers in the Ultraviolet Spectrum

description: The adiabatic PECs of XH+ (X = Na, K, Rb, Cs)The total photodissociation cross sections of NaH+, KH+, RbH+ and CsH+ at thermodynamic temperatures of 0 K, 500 K, 1000 K, 5000 K and 10000 K, respectively.<br>
DOI: 10.21233/ewag-7k98
title: Danaher Bog pollen dataset

description: Raw data for the Danaher Bog pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/1heb-p928
title: Burns Bog testate amoebae surface sample dataset

description: Raw data for the Burns Bog testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.fauuhw
title: Occurrence Download

description: A dataset containing 847860 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 1973-1993"
 ]
}

 The dataset includes 847860 records from 427 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026212-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/3h7q-1g04
title: Oksan-Ri ostracode surface sample dataset

description: Raw data for the Oksan-Ri ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/wt38-4123
title: Daarle I pollen dataset

description: Raw data for the Daarle I pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/xxmy-2v62
title: Forez site 18 pollen surface sample dataset

description: Raw data for the Forez site 18 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/4yt4-v947
title: Lake of the Woods pollen surface sample dataset

description: Raw data for the Lake of the Woods pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/ky9k-d391
title: Salter Sitch pollen dataset

description: Raw data for the Salter Sitch pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/gmsy-9019
title: 30 [HFL30] water chemistry dataset

description: Raw data for the 30 [HFL30] water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/1d14-wa50
title: Trout Peatland H testate amoebae surface sample dataset

description: Raw data for the Trout Peatland H testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/7kta-cg31
title: LDDsite1146 ostracode surface sample dataset

description: Raw data for the LDDsite1146 ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/4mwk-z749
title: B9535 pollen surface sample dataset

description: Raw data for the B9535 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.abyw4z
title: Occurrence Download

description: A dataset containing 89 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 countrycode countrycode,
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, countrycode, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, countrycode, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, countrycode, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, countrycode, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, countrycode, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, countrycode, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'IT'
 AND (occurrence.taxonkey = 5298 OR occurrence.acceptedtaxonkey = 5298 OR occurrence.kingdomkey = 5298 OR occurrence.phylumkey = 5298 OR occurrence.classkey = 5298 OR occurrence.orderkey = 5298 OR occurrence.familykey = 5298 OR occurrence.genuskey = 5298 OR occurrence.specieskey = 5298)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year",
 occurrence.countrycode

 The dataset's 89 records were derived from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026228-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/k89y-dh21
title: LDDsite3196 water chemistry dataset

description: Raw data for the LDDsite3196 water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/0pws-qx10
title: Crystal P. diatom surface sample dataset

description: Raw data for the Crystal P. diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.