Showing 23 of total 23 results (show query)
xrobin
pROC:Display and Analyze ROC Curves
Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.
Maintained by Xavier Robin. Last updated 5 months ago.
bootstrappingcovariancehypothesis-testingmachine-learningplotplottingrocroc-curvevariancecpp
125 stars 15.18 score 16k scripts 445 dependents
bioc
DirichletMultinomial:Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data
Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.
Maintained by Martin Morgan. Last updated 5 months ago.
immunooncologymicrobiomesequencingclusteringclassificationmetagenomicsgsl
10 stars 10.91 score 125 scripts 26 dependents
thie1e
cutpointr:Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks
Estimate cutpoints that optimize a specified metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included. For an overview of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.
Maintained by Christian Thiele. Last updated 4 months ago.
bootstrappingcutpoint-optimizationroc-curvecpp
88 stars 10.44 score 322 scripts 1 dependents
spatstat
spatstat.explore:Exploratory Data Analysis for the 'spatstat' Family
Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.
Maintained by Adrian Baddeley. Last updated 9 days ago.
cluster-detectionconfidence-intervalshypothesis-testingk-functionroc-curvesscan-statisticssignificance-testingsimulation-envelopesspatial-analysisspatial-data-analysisspatial-sharpeningspatial-smoothingspatial-statistics
1 stars 10.18 score 67 scripts 150 dependents
babaknaimi
sdm:Species Distribution Modelling
An extensible framework for developing species distribution models using individual and community-based approaches, generate ensembles of models, evaluate the models, and predict species potential distributions in space and time. For more information, please check the following paper: Naimi, B., Araujo, M.B. (2016) <doi:10.1111/ecog.01881>.
Maintained by Babak Naimi. Last updated 2 months ago.
24 stars 9.31 score 312 scripts 1 dependents
irinagain
iglu:Interpreting Glucose Data from Continuous Glucose Monitors
Implements a wide range of metrics for measuring glucose control and glucose variability based on continuous glucose monitoring data. The list of implemented metrics is summarized in Rodbard (2009) <doi:10.1089/dia.2009.0015>. Additional visualization tools include time-series plots, lasagna plots and ambulatory glucose profile report.
Maintained by Irina Gaynanova. Last updated 23 days ago.
26 stars 9.00 score 39 scripts
gavinsimpson
analogue:Analogue and Weighted Averaging Methods for Palaeoecology
Fits Modern Analogue Technique and Weighted Averaging transfer function models for prediction of environmental data from species data, and related methods used in palaeoecology.
Maintained by Gavin L. Simpson. Last updated 6 months ago.
14 stars 8.87 score 185 scripts 4 dependentsbioc
iCOBRA:Comparison and Visualization of Ranking and Assignment Methods
This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. Various types of performance plots can be generated programmatically. The package also contains a shiny application for interactive exploration of results.
Maintained by Charlotte Soneson. Last updated 3 months ago.
14 stars 8.86 score 192 scripts 1 dependents
flr
FLCore:Core Package of FLR, Fisheries Modelling in R
Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.
Maintained by Iago Mosqueira. Last updated 9 days ago.
fisheriesflrfisheries-modelling
16 stars 8.78 score 956 scripts 23 dependents
minatonakazawa
fmsb:Functions for Medical Statistics Book with some Demographic Data
Several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.
Maintained by Minato Nakazawa. Last updated 1 years ago.
3 stars 7.74 score 1.9k scripts 23 dependents
rezamoammadi
BDgraph:Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Advanced statistical tools for Bayesian structure learning in undirected graphical models, accommodating continuous, ordinal, discrete, count, and mixed data. It integrates recent advancements in Bayesian graphical models as presented in the literature, including the works of Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2021) <doi:10.1080/01621459.2021.1996377>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, and Mohammadi et al. (2023) <doi:10.48550/arXiv.2307.00127>.
Maintained by Reza Mohammadi. Last updated 7 months ago.
8 stars 7.46 score 223 scripts 7 dependents
fcharte
mldr:Exploratory Data Analysis and Manipulation of Multi-Label Data Sets
Exploratory data analysis and manipulation functions for multi- label data sets along with an interactive Shiny application to ease their use.
Maintained by David Charte. Last updated 5 years ago.
23 stars 7.07 score 168 scripts 2 dependents
ballings
AUC:Threshold Independent Performance Measures for Probabilistic Classifiers
Various functions to compute the area under the curve of selected measures: The area under the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the receiver operating characteristic curve (AUROC). Support for visualization and partial areas is included.
Maintained by Michel Ballings. Last updated 3 years ago.
5.37 score 424 scripts 7 dependentsbioc
CMA:Synthesis of microarray-based classification
This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.
Maintained by Roman Hornung. Last updated 5 months ago.
5.09 score 61 scripts
iangow
farr:Data and Code for Financial Accounting Research
Handy functions and data to support a course book for accounting research. Gow, Ian D. and Tongqing Ding (2024) 'Empirical Research in Accounting: Tools and Methods' <https://iangow.github.io/far_book/>.
Maintained by Ian Gow. Last updated 2 months ago.
17 stars 5.05 score 66 scripts
tesselle
kairos:Analysis of Chronological Patterns from Archaeological Count Data
A toolkit for absolute and relative dating and analysis of chronological patterns. This package includes functions for chronological modeling and dating of archaeological assemblages from count data. It provides methods for matrix seriation. It also allows to compute time point estimates and density estimates of the occupation and duration of an archaeological site.
Maintained by Nicolas Frerebeau. Last updated 25 days ago.
chronologymatrix-seriationarchaeologyarchaeological-science
4.66 score 11 scripts 1 dependents
foucher-y
survivalSL:Super Learner for Survival Prediction from Censored Data
Several functions and S3 methods to construct a super learner in the presence of censored times-to-event and to evaluate its prognostic capacities.
Maintained by Yohann Foucher. Last updated 2 months ago.
2 stars 3.70 score
aijordan
triptych:Diagnostic Graphics to Evaluate Forecast Performance
Overall predictive performance is measured by a mean score (or loss), which decomposes into miscalibration, discrimination, and uncertainty components. The main focus is visualization of these distinct and complementary aspects in joint displays. See Dimitriadis, Gneiting, Jordan, Vogel (2024) <doi:10.1016/j.ijforecast.2023.09.007>.
Maintained by Alexander I. Jordan. Last updated 10 months ago.
3.28 score 19 scripts
mathijsdeen
MDMA:Mathijs Deen's Miscellaneous Auxiliaries
Provides a variety of functions useful for data analysis, selection, manipulation, and graphics.
Maintained by Mathijs Deen. Last updated 10 days ago.
2.70 score
cran
longROC:Time-Dependent Prognostic Accuracy with Multiply Evaluated Bio Markers or Scores
Time-dependent Receiver Operating Characteristic curves, Area Under the Curve, and Net Reclassification Indexes for repeated measures. It is based on methods in Barbati and Farcomeni (2017) <doi:10.1007/s10260-017-0410-2>.
Maintained by Alessio Farcomeni. Last updated 7 years ago.
1.00 score
yangfengstat
pgraph:Build Dependency Graphs using Projection
Implements a general framework for creating dependency graphs using projection as introduced in Fan, Feng and Xia (2019)<arXiv:1501.01617>. Both lasso and sparse additive model projections are implemented. Both Pearson correlation and distance covariance options are available to generate the graph.
Maintained by Yang Feng. Last updated 5 years ago.
1 stars 1.00 score 3 scriptscran
regRSM:Random Subspace Method (RSM) for Linear Regression
Performs Random Subspace Method (RSM) for high-dimensional linear regression to obtain variable importance measures. The final model is chosen based on validation set or Generalized Information Criterion.
Maintained by Pawel Teisseyre. Last updated 10 years ago.
1 stars 1.00 score