cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jq4nch
title: Occurrence Download

description: A dataset containing 141054 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aedes albopictus"
 ]
}

 The dataset includes 141054 records from 220 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065176-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rmgnrk
title: Occurrence Download

description: A dataset containing 24806506 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pyrus tamamschianae, Pyrus acutiserrata, Pyrus armeniacifolia, Pyrus asiae-mediae, Pyrus betulifolia, Pyrus boissieriana, Pyrus bourgaeana, Pyrus bretschneideri, Pyrus browiczii, Pyrus cajon, Pyrus calleryana, Pyrus castribonensis, Pyrus chosrovica, Pyrus ciancioi, Pyrus communis, Pyrus complexa, Pyrus cordata, Pyrus daralagezi, Pyrus demetrii, Pyrus elaeagrifolia, Rosaceae, Pyrus fedorovii, Pyrus georgica, Pyrus gergerana, Pyrus grossheimii, Pyrus hajastana, Pyrus hakkiarica, Pyrus hopeiensis, Pyrus hyrcana, Pyrus ketzkhovelii, Pyrus korshinskyi, Pyrus megrica, Pyrus nivalis, Pyrus nutans, Pyrus oxyprion, Pyrus pashia, Pyrus phaeocarpa, Pyrus pseudopashia, Pyrus pyrifolia, Pyrus raddeana, Pyrus regelii, Pyrus sachokiana, Pyrus salicifolia, Pyrus serrulata, Pyrus sicanorum, Pyrus sosnovskyi, Pyrus spinosa, Pyrus syriaca, Pyrus tadshikistanica, Pyrus taihangshanensis, Pyrus taiwanensis, Pyrus takhtadzhianii, Pyrus theodorovii, Pyrus turcomanica, Pyrus ussuriensis, Pyrus vallis-demonis, Pyrus voronovii, Pyrus vsevolodovii, Pyrus xerophila, Pyrus zangezura)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24806506 records from 7764 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065187-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ww69zq
title: Occurrence Download

description: A dataset containing 325 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Araucaria cunninghamii Aiton ex D.Don"
 ]
}

 The dataset includes 325 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039605-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4h4tax
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Pristimantis guaiquinimensis (Schlüter & Rödder, 2007)"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045826-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yz4zxm
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Disa sabulosa Bolus"
 ]
}

 The dataset includes 64 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034593-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8jlmfo
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhinobatos percellens (Walbaum, 1792)",
 "Country is Colombia"
 ]
}

 The dataset includes 19 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010050-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dqemqf
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Philautus poecilius Brown & Alcala, 1994"
 ]
}

 The dataset includes 56 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045805-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h2hsy6
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Disa rungweensis Schltr."
 ]
}

 The dataset includes 27 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034582-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rrivp0
title: Occurrence Download

description: A dataset containing 238 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus pinceana Gordon",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 238 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010050-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p5m377
title: Occurrence Download

description: A dataset containing 180876 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyanerpes cyaneus (Linnaeus, 1766)"
 ]
}

 The dataset includes 180876 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045812-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nf86j9
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dryopteris gorgonea J.P.Roux"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034583-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mo3zgc
title: Occurrence Download

description: A dataset containing 778 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chrysocyon brachyurus (Illiger, 1815)"
 ]
}

 The dataset includes 778 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010599-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.thujhk
title: Occurrence Download

description: A dataset containing 344 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chamaesipho columna (Spengler, 1790)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is MANAGED"
 ]
 }
 },
 {
 "not" : {
 "EstablishmentMeans" : [
 "is not null"
 ]
 }
 }
 ]
 },
 {
 "or" : [
 "OccurrenceStatus is Present",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is not null"
 ]
 }
 }
 ]
 }
 ]
}

 The dataset includes 344 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045878-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2w34ud
title: Occurrence Download

description: A dataset containing 5843 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Hylophilus amaurocephalus (Nordmann, 1835)"
 ]
}

 The dataset includes 5843 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034607-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gtvz53
title: Occurrence Download

description: A dataset containing 3030542 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aythya fuligula (Linnaeus, 1758)"
 ]
}

 The dataset includes 3030542 records from 1221 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034608-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vl2m9n
title: Occurrence Download

description: A dataset listing the 6 species recorded in GBIF matching the query:
{
 "and" : [
 "Year 1915-2012",
 "HasCoordinate is true",
 "TaxonKey is Lobatostoma Eckmann, 1932",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 6 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010605-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pe9fqh
title: Occurrence Download

description: A dataset containing 370505 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Grimothea monodon (H.Milne-Edwards, 1837)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is MANAGED"
 ]
 }
 },
 {
 "not" : {
 "EstablishmentMeans" : [
 "is not null"
 ]
 }
 }
 ]
 },
 {
 "or" : [
 "OccurrenceStatus is Present",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is not null"
 ]
 }
 }
 ]
 }
 ]
}

 The dataset includes 370505 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053625-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28395114
title: Fast Signal Region Detection With Application to Whole Genome Association Studies

description: Research on the localization of the genetic basis associated with diseases or traits has been widely conducted in the last few decades. Scan methods have been developed for region-based analysis in whole-genome association studies, helping us better understand how genetics influences human diseases or traits, especially when the aggregated effects of multiple causal variants are present. In this paper, we propose a fast and effective algorithm coupling with high-dimensional test for simultaneously detecting multiple signal regions, which is distinct from existing methods using scan or knockoff statistics. The idea is to conduct binary splitting with re-search and arrangement based on a sequence of dynamic critical values to increase detection accuracy and reduce computation. Theoretical and empirical studies demonstrate that our approach enjoys favorable theoretical guarantees with fewer restrictions and exhibits superior numerical performance with faster computation. Utilizing the UK Biobank data to identify the genetic regions related to breast cancer, we confirm previous findings and meanwhile, identify a number of new regions that suggest strong associations with risk of breast cancer and deserve further investigation. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28334949
title: Phase-Type Distributions for Sieve Estimation

description: In many semiparametric models, the infinite-dimensional parameter of direct interest is a probability density, but its nonparametric estimation is usually difficult in the presence of incomplete data. To address this issue, this study promotes phase-type distributions as a method of sieve. Phase-type distributions are dense in the space of nonnegative distributions, closed under minimum, maximum, and convolution, and compatible with the accelerated failure time model. This renders them attractive for sieve density estimation for problems with sophisticated missing data. However, the class of phase-type distributions is over-parameterized, and its approximation error rate for a given density as the number of phases increases remains unknown. These handicaps hinder its theoretical development as a sieve method. In this article, we design a sieve class of identifiable phase-type densities and establish its approximation error rate for a given density, which is the first error rate result known for phase type distributions. The proposed sieve is then used for semiparametric M-estimation, where the nonparametric component is a density. Building on the approximation error rate results, we establish general asymptotic properties of the phase-type sieve estimators and apply them to models that have complicated data missingness and cannot be easily handled by existing methods. Our simulation and real data analysis focus on right-censored data with missing indicators, in which we demonstrate that our estimators are more efficient than existing estimators. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28395114.v1
title: Fast Signal Region Detection with Application to Whole Genome Association Studies

description: Research on the localization of the genetic basis associated with diseases or traits has been widely conducted in the last few decades. Scan methods have been developed for region-based analysis in whole-genome association studies, helping us better understand how genetics influences human diseases or traits, especially when the aggregated effects of multiple causal variants are present. In this paper, we propose a fast and effective algorithm coupling with high-dimensional test for simultaneously detecting multiple signal regions, which is distinct from existing methods using scan or knockoff statistics. The idea is to conduct binary splitting with re-search and arrangement based on a sequence of dynamic critical values to increase detection accuracy and reduce computation. Theoretical and empirical studies demonstrate that our approach enjoys favorable theoretical guarantees with fewer restrictions and exhibits superior numerical performance with faster computation. Utilizing the UK Biobank data to identify the genetic regions related to breast cancer, we confirm previous findings and meanwhile, identify a number of new regions that suggest strong associations with risk of breast cancer and deserve further investigation.
DOI: 10.15468/dl.h5yuck
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mangifera kemanga Blume",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 13 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008585-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28334883
title: Deep Regression for Repeated Measurements

description: Nonparametric mean function regression with repeated measurements serves as a cornerstone for many statistical branches, such as longitudinal/panel/functional data analysis. In this work, we investigate this problem using fully connected deep neural network (DNN) estimators with flexible shapes. A novel theoretical framework allowing arbitrary sampling frequency is established by adopting empirical process techniques to tackle clustered dependence. We then consider the DNN estimators for Hölder target function and illustrate a key phenomenon, the phase transition in the convergence rate, inherent to repeated measurements and its connection to the curse of dimensionality. Furthermore, we study several examples with low intrinsic dimensions, including the hierarchical composition model, low-dimensional support set and anisotropic Hölder smoothness. We also obtain new approximation results and matching lower bounds to demonstrate the adaptivity of the DNN estimators for circumventing the curse of dimensionality. Simulations and real data examples are provided to support our theoretical findings and practical implications. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28325389
title: Estimation of Over-Parameterized Models from an Auto-Modeling Perspective

description: From a model-building perspective, we propose a paradigm shift for fitting over-parameterized models. Philosophically, the mindset is to fit models to future observations rather than to the observed sample. Technically, given an imputation method to generate future observations, we fit over-parameterized models to these future observations by optimizing an approximation of the desired expected loss function based on its sample counterpart and an adaptive <i>duality function</i>. The required imputation method is also developed using the same estimation technique with an adaptive <i>m</i>-out-of-<i>n</i> bootstrap approach. We illustrate its applications with the many-normal-means problem, n&lt;p linear regression, and neural network-based image classification of MNIST digits. The numerical results demonstrate its superior performance across these diverse applications. While primarily expository, the article conducts an in-depth investigation into the theoretical aspects of the topic. It concludes with remarks on some open problems. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28325389.v1
title: Estimation of Over-parameterized Models from an Auto-Modeling Perspective

description: From a model-building perspective, we propose a paradigm shift for fitting over-parameterized models. Philosophically, the mindset is to fit models to future observations rather than to the observed sample. Technically, given an imputation method to generate future observations, we fit over-parameterized models to these future observations by optimizing an approximation of the desired expected loss function based on its sample counterpart and an adaptive <i>duality function</i>. The required imputation method is also developed using the same estimation technique with an adaptive m-out-of-n bootstrap approach. We illustrate its applications with the many-normal-means problem, n&lt;p linear regression, and neural network-based image classification of MNIST digits. The numerical results demonstrate its superior performance across these diverse applications. While primarily expository, the paper conducts an in-depth investigation into the theoretical aspects of the topic. It concludes with remarks on some open problems.
DOI: 10.15468/dl.cnvxb6
title: Occurrence Download

description: A dataset containing 32560 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lepidium campestre (L.) W.T.Aiton)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 32560 records from 877 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008583-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvs5ew
title: Occurrence Download

description: A dataset containing 430 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Lophophorus lhuysii Geoffroy Saint-A.Hilaire, 1866",
 "Year 2000-2024"
 ]
}

 The dataset includes 430 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016349-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.