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Dataset results
144 results for “statistical model”
Population average skull model obtained by means of statistical shape modelling
<p>Sagittal Craniosynostosis (SC) is a congenital condition whereby the newborn skull develops abnormally due to premature ossification of the sagittal suture. Spring-assisted cranioplasty (SAC) is a minimally invasive surgical technique to treat SC where metallic distractors are used to reshape the newborn's head. Although safe and effective, SAC outcomes remain uncertain due to the limited understanding of skull-distractor interaction and limited information provided by the analysis of single surgical cases.</p> <p>Hereby, an SC population average skull model was created to simulate spring insertion by means of finite element analysis.</p>
Highlighting the potential of multilevel statistical models for analysis of individual agroforestry systems (companion working R code)
<p>A companion working R code and crop yield dataset that illustrate key concepts presented in a scientific publication titled 'Highlighting the potential of multilevel statistical models for analysis of individual agroforestry systems' published in Agroforestry Systems (July 2023). For the shape file of tree strips, please refer to the publication's supplementary material (adjust the name accordingly). </p>
Data from: Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines
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Data from: Modelling competition and dispersal in a statistical phylogeographic framework
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Data from: The relationship between native species richness and exotic species richness or occurrence will always be negative when the total number of species is accounted for in statistical models: A response to Beaury et al.
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Bayesian inference of tree species using diffusion models: tabulated posterior statistics for SNAPP and SNAPPER analyses
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Data from: Spatially structured statistical network models for landscape genetics
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Data from: How does evolutionary variation in basal metabolic rates arise? A statistical assessment and a mechanistic model
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Population average skull model obtained by means of statistical shape modelling
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Data from: Evaluating predictive performance of statistical models explaining wild bee abundance in a mass-flowering crop
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Model data for "A hybrid dynamical-statistical model for advancing subseasonal tropical cyclone prediction over the western North Pacific"
<p>The dataset is the potential predictors of the statistical forecast model based on the 4 methods.</p> <p>The files in the document named "Train" are the potential predictors and TC anomalous counts for C1-C7 and TCall in the training period of 1979-2002 with 480-time points. For example, "./data/Train/M1/prepar/Obs_C1_pre-data.txt" contains 7 potential predictors of OLR, SSTA, specific humidity at 700 hPa, omega at 500 hPa, divergence and vorticity at 850hPa defined with method 1, and TC anomalous for TC of C1 prediction.</p> <p>The files named "Model_Lead*_C*_pre-data_*.txt" in "Frcst" the document are the potential predictors in the forecast period of 2003-2013 at lead times of 10, 15, 20, 25, 30, and 35 days with 220-time points. For example, "./data/Frcst/M1/prepar/Model_Lead10_C1_pre-data_00.txt" contains 7 potential predictors from the output of the FLOR model at lead 10 days initialized at Z00 time defined with method 1. Besides, "./data/Frcst/M1/prepar/Obs_C1_pre-data.txt" contains 7 potential predictors from the observation, which is the result of lead 0 days.</p>
Repository for: "Extreme statistic and extreme events in dynamical models of turbulence"
<div>This repository contains underlying data, post-processing scripts and figure scripts, corresponding to the article "Extreme statistic and extreme events in dynamical models of turbulence", X.M. de Wit, G. Ortali, A. Corbetta, A.A. Mailybaev, L. Biferale, F. Toschi, 2024, Phys. Rev. E 109 (5), 055106.</div> <div> </div> <div><strong>Data</strong></div> <div>Raw data of the obtained moments and histogram of the structure function are provided in 'PRODUCTION/STAT_RUNS/' and 'VALIDATION/STAT_RUNS/' respectively for the production runs and validation runs.</div> <div> </div> <div><strong>Post-processing</strong></div> <div>Various post-processing routines for e.g. the computation of the anomalous scaling exponents are provided in the Jupyter notebooks 'PROD_process.ipynb' and 'VALI_*_process.ipynb' respectively for the production runs and validation runs. The computation of the singularity spectrum is provided in 'PROD_singularity_spec.ipynb'.</div> <div> </div> <div><strong>Figures</strong></div> <div>Reproduction of the figures as appearing in the paper can be done using the corresponding Jupyter notebooks labeled as 'PAPER_*.ipynb'.</div>
Figure 3 in Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan
Figure 3. Plots of R2(a), adjusted R2(b), C (c) and MSE (d) against P. p
Figure 1 in Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan
Figure 1. Normal probability plot of residuals.
Post EVAR Endoleak Detection : Model-based Iterative Reconstruction (MBIR) vs Adaptive Statistical Iterative Reconstruction (ASIR) CTA; a Prospective Study
ClinicalTrials.gov study NCT02082834. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Virtual Anatomical Reconstruction of Mandibular Bone Defects Using a Statistical Shape Model
ClinicalTrials.gov study NCT04475237. IPD Sharing: NO. Countries: 1. Publications: 0.
Model-based Iterative Reconstruction (MB-IR VEOTM) in Ultra Low-dose Abdominal CT Versus Adaptative Statistical Iterative Reconstruction (ASIR): A Prospective Study for Acute Renal Colic
ClinicalTrials.gov study NCT02076737. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Sea-ice Thickness and Draft Statistics from Submarine ULS, Moored ULS, and a Coupled Model, Version 1
This data set consists of estimates of mean values of sea-ice thickness and sea-ice draft in meters computed from three different input data sets: sea ice draft from Upward Looking Sonar (ULS) mounted on submarines, sea ice draft from ULS mounted on bottom-anchored moorings, and a simulated ice-thickness model. The data span from 1979 to 2004 and cover two regions centered around the North Pole.
Combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer with CancerInSilico
GEO Series GSE114375. Homo sapiens. 90 samples. Type: Expression profiling by array.
robust statistical modeling improves sensitivity of high-throughput rnA structure probing experiments
GEO Series GSE78208. Saccharomyces cerevisiae. 4 samples. Type: Other.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.