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Showing 8 open source projects for "estimates"
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ConformalPrediction.jl
Predictive Uncertainty Quantification through Conformal Prediction
...Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use of dedicated calibration data. -
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Lasso.jl
Lasso/Elastic Net linear and generalized linear models
Lasso.jl is a pure Julia implementation of the glmnet coordinate descent algorithm for fitting linear and generalized linear Lasso and Elastic Net models. -
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FiniteDifferences.jl
High accuracy derivatives, estimated via numerical finite differences
FiniteDifferences.jl estimates derivatives with finite differences. See also the Python package FDM. FiniteDiff.jl and FiniteDifferences.jl are similar libraries: both calculate approximate derivatives numerically. You should definitely use one or the other, rather than the legacy Calculus.jl finite differencing, or reimplementing it yourself. At some point in the future, they might merge, or one might depend on the other. -
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see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It... -
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Cubature.jl
One- and multi-dimensional adaptive integration routines for Julia
...Adaptive integration works by evaluating the integrand at more and more points until the integrand converges to a specified tolerance (with the error estimated by comparing integral estimates with different numbers of points). The Cubature module implements two schemes for this adaptation: h-adaptivity (routines hquadrature, hcubature, hquadrature_v, and hcubature_v) and p-adaptivity (routines pquadrature, pcubature, pquadrature_v, and pcubature_v). The h- and p-adaptive routines accept the same parameters, so you can use them interchangeably, but they have very different convergence characteristics. -
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ImagingAnalysis
Direct tissue-level image quantification package for Mathematica
ImagingAnalysis is a Mathematica package that performs grid-based analysis of time-lapse imaging data saved in a sequence of TIFF files. This package requires Mathematica 7.0. Revised on 14 May 2017: Bugs are fixed and incompatibility issues are resolved. The current version runs on Mathematica 11. -
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SVG_plot
Plot data in SVG format using C++ library
...It has been maintained and enhanced since then in Boost Sandbox, but is judged unsuitable for a Boost Library, so now being made more widely available here. Version 2 adds representation of uncertainty estimates as numbers and zones. -
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Graph representation of the parapsychological (scientific) models and propositions. The graph will help to visualize the relation between the diferent hypothesis and estimates the level of confidence of a given hypothesis or model.
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