Showing 11 of total 11 results (show query)
tidymodels
yardstick:Tidy Characterizations of Model Performance
Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).
Maintained by Emil Hvitfeldt. Last updated 21 days ago.
387 stars 15.47 score 2.2k scripts 60 dependents
bioc
genefilter:genefilter: methods for filtering genes from high-throughput experiments
Some basic functions for filtering genes.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
11.11 score 2.4k scripts 143 dependents
rbgramacy
tgp:Bayesian Treed Gaussian Process Models
Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear models, CART, treed linear models, stationary separable and isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions (with projection and slice capabilities) and tree drawing, designed for visualization of tgp-class output. Sensitivity analysis and multi-resolution models are supported. Sequential experimental design and adaptive sampling functions are also provided, including ALM, ALC, and expected improvement. The latter supports derivative-free optimization of noisy black-box functions. For details and tutorials, see Gramacy (2007) <doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010) <doi:10.18637/jss.v033.i06>.
Maintained by Robert B. Gramacy. Last updated 7 months ago.
9 stars 7.39 score 203 scripts 13 dependents
kkawato
rdlearn:Safe Policy Learning under Regression Discontinuity Design with Multiple Cutoffs
Implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The 'rdlearn' package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.
Maintained by Kentaro Kawato. Last updated 1 months ago.
1 stars 5.23 score 4 scripts
iainmstott
popdemo:Demographic Modelling Using Projection Matrices
Tools for modelling populations and demography using matrix projection models, with deterministic and stochastic model implementations. Includes population projection, indices of short- and long-term population size and growth, perturbation analysis, convergence to stability or stationarity, and diagnostic and manipulation tools.
Maintained by Iain Stott. Last updated 3 years ago.
5.16 score 172 scripts 7 dependents
doebler
mada:Meta-Analysis of Diagnostic Accuracy
Provides functions for diagnostic meta-analysis. Next to basic analysis and visualization the bivariate Model of Reitsma et al. (2005) that is equivalent to the HSROC of Rutter & Gatsonis (2001) can be fitted. A new approach based to diagnostic meta-analysis of Holling et al. (2012) is also available. Standard methods like summary, plot and so on are provided.
Maintained by Philipp Doebler. Last updated 3 years ago.
2 stars 5.09 score 58 scripts 3 dependents
mdtrinh
paths:An Imputation Approach to Estimating Path-Specific Causal Effects
In causal mediation analysis with multiple causally ordered mediators, a set of path-specific effects are identified under standard ignorability assumptions. This package implements an imputation approach to estimating these effects along with a set of bias formulas for conducting sensitivity analysis (Zhou and Yamamoto <doi:10.31235/osf.io/2rx6p>). It contains two main functions: paths() for estimating path-specific effects and sens() for conducting sensitivity analysis. Estimation uncertainty is quantified using the nonparametric bootstrap.
Maintained by Minh Trinh. Last updated 4 years ago.
3.71 score 102 scripts
jgaeb
rar:Risk-Adjusted Regression
Perform risk-adjusted regression and sensitivity analysis as developed in "Mitigating Omitted- and Included-Variable Bias in Estimates of Disparate Impact" Jung et al. (2024) <arXiv:1809.05651>.
Maintained by Johann Gaebler. Last updated 1 years ago.
1 stars 2.70 score 5 scripts
r-forge
softclassval:Soft Classification Performance Measures
An extension of sensitivity, specificity, positive and negative predictive value to continuous predicted and reference memberships in [0, 1].
Maintained by C. Beleites. Last updated 9 years ago.
2.00 score 8 scriptsrbgramacy
dynaTree:Dynamic Trees for Learning and Design
Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential design and optimization, fully online learning with drift, variable selection, and sensitivity analysis of inputs. Illustrative examples from the original dynamic trees paper (Gramacy, Taddy & Polson (2011); <doi:10.1198/jasa.2011.ap09769>) are facilitated by demos in the package; see demo(package="dynaTree").
Maintained by Robert B. Gramacy. Last updated 7 months ago.
2 stars 1.66 score 23 scripts
