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ShareScore release 0.9.0
Dataset results
34 results for “least squares”
Data from: A method for assessing phylogenetic least squares models for shape and other high-dimensional multivariate data
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Data from: Fast dating using least-squares criteria and algorithms
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Parkinson’s disease propagation using MRI biomarkers and partial least squares path modeling
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Data from: Compressor map regression modelling based on partial least squares
In this work, two kinds of partial least squares modelling methods are applied to predict a compressor map: one uses a Power function polynomial as the basis function (PLSO), and the other uses a trigonometric function polynomial (PLSN). To demonstrate the potential capabilities of PLSO and PLSN for a typical interpolated prediction and extrapolated prediction, they are compared with two other classical data-driven modelling methods, namely, the look-up table and artificial neural network. PLSO and PLSN are also compared to each other. The results show that PLSO and PLSN have a better prediction performance than the look-up table and the artificial neural network, especially for the extrapolated prediction. At the same time, the computational time is also decreased sharply. Compared with PLSO, PLSN is characterized with higher prediction accuracy and shorter computational time than PLSO. It can be expected that PLSN can be time-saving and improve the accuracy of a thermodynamic model of a diesel engine.
Data from: A prediction model of compressor with variable geometry diffuser based on elliptic equation and Partial Least Squares
In order to fulfill more and more extensive intake air flow range of diesel engine, variable geometry compressor (VGC) is introduced into turbocharged diesel engine. However, due to the variable diffuser vanes angle (DVA), the prediction for the performance of VGC becomes more difficult than normal compressor. In the present study, a prediction model comprised of elliptical equation and PLS (Partial Least Squares) model was proposed to predict the performance of VGC. The speed lines of pressure ratio map and efficiency map with elliptical equation were fitted, and the coefficients of elliptical equation was introduced into PLS model to build the polynomial relationship between the coefficients and relative speed, DVA. And further, the maximal order of polynomical was detailed investigated to reduce the number of sub-coefficients and acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority in compressor performance prediction, the prediction results of this model were compared with those of look-up table and BPNN. The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than look-up table and BPNN under the same condition in the VGA performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.
Data from: Time-dependent speciation and extinction from phylogenies: a least squares approach
Molecular phylogenies contribute to the study of the patterns and processes of macroevolution even though past events (fossils) are not recorded in these data. In this paper, I consider the general time-dependent birth–death model in order to fit any model of temporal variation in speciation and extinction to phylogenies. I establish formulae to compute the expected cumulative distribution function of branching times for any model, and, building on previous published works, I derive maximum likelihood estimators. Some limitations of the likelihood approach are described, and a fitting procedure based on least squares is developed that alleviates the shortcomings of maximum likelihood in the present context. Parametric and nonparametric bootstrap procedures are developed to assess uncertainty in the parameter estimates, the latter version giving narrower confidence intervals and being faster to compute. I also present several general algorithms of tree simulation in continuous time. I illustrate the application of this approach with the analysis of simulated data sets, and two published phylogenies of primates (Catarrhinae) and lizards (Agamidae).
Data from: Compressor map regression modelling based on partial least squares
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Data from: Time-dependent speciation and extinction from phylogenies: a least squares approach
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Data from: A prediction model of compressor with variable geometry diffuser based on elliptic equation and Partial Least Squares
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Deep-unrolling architecture for image-domain least-squares migration
<p>A general deep-unrolling architecture is proposed to solve the ill-posed inverse problem in the geophysical community. We apply the DU architecture to image-domain least-squares migration, which can provide improved reflectivity estimates. Moreover, the DU architecture can regularize the inversion process and can produce a qualitative measure of the uncertainty. The zip file "DU-IDLSM.rar" is the code of Python for DU-IDLSM and "data.rar" is bin data for DU-IDLSM. </p>
Partial Least Squares Regression Modelling for Glaucoma Detection
ClinicalTrials.gov study NCT03365245. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Predicting Intraocular Lens Tilt Using OCT Measurements and Partial Least Squares Regression Modelling
ClinicalTrials.gov study NCT06305338. IPD Sharing: NO. Countries: 1. Publications: 0.
Predicting Lens Tilt Using Optical Coherence Tomography and Partial Least Squares Regression Modelling
ClinicalTrials.gov study NCT05915429. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: The mediating effect of perceived Coach's emotional support to Life satisfaction, Curiosity and Sports engagement: a Partial Least Square-Structural Equation Model
<p>This data set is from the study titled, "The mediating effect of perceived Coach’s emotional support to Life satisfaction, Curiosity and Sports engagement: a Partial Least Square-Structural Equation Model."</p>
ScienceDex guides
Understand access before you commit
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.