R-universe search: exports:density

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adriancorrendo

metrica:Prediction Performance Metrics

A compilation of more than 80 functions designed to quantitatively and visually evaluate prediction performance of regression (continuous variables) and classification (categorical variables) of point-forecast models (e.g. APSIM, DSSAT, DNDC, supervised Machine Learning). For regression, it includes functions to generate plots (scatter, tiles, density, & Bland-Altman plot), and to estimate error metrics (e.g. MBE, MAE, RMSE), error decomposition (e.g. lack of accuracy-precision), model efficiency (e.g. NSE, E1, KGE), indices of agreement (e.g. d, RAC), goodness of fit (e.g. r, R2), adjusted correlation coefficients (e.g. CCC, dcorr), symmetric regression coefficients (intercept, slope), and mean absolute scaled error (MASE) for time series predictions. For classification (binomial and multinomial), it offers functions to generate and plot confusion matrices, and to estimate performance metrics such as accuracy, precision, recall, specificity, F-score, Cohen's Kappa, G-mean, and many more. For more details visit the vignettes <https://adriancorrendo.github.io/metrica/>.

Maintained by Adrian A. Correndo. Last updated 9 months ago.

77 stars 7.88 score 49 scripts

aalfons

robmed:(Robust) Mediation Analysis

Perform mediation analysis via the fast-and-robust bootstrap test ROBMED (Alfons, Ates & Groenen, 2022a; <doi:10.1177/1094428121999096>), as well as various other methods. Details on the implementation and code examples can be found in Alfons, Ates, and Groenen (2022b) <doi:10.18637/jss.v103.i13>. Further discussion on robust mediation analysis can be found in Alfons & Schley (2024) <doi:10.31234/osf.io/2hqdy>.

Maintained by Andreas Alfons. Last updated 1 months ago.

6 stars 6.35 score 31 scripts 1 dependents

wkostelecki

ezplot:Functions for Common Chart Types

Wrapper for the 'ggplot2' package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.

Maintained by Wojtek Kostelecki. Last updated 7 months ago.

5 stars 6.16 score 116 scripts

andreanini

idiolect:Forensic Authorship Analysis

Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.

Maintained by Andrea Nini. Last updated 25 days ago.

14 stars 6.12 score 3 scripts

bioc

PLSDAbatch:PLSDA-batch

A novel framework to correct for batch effects prior to any downstream analysis in microbiome data based on Projection to Latent Structures Discriminant Analysis. The main method is named “PLSDA-batch”. It first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data whilst preserving biological variation of interest. PLSDA-batch is highly suitable for microbiome data as it is non-parametric, multivariate and allows for ordination and data visualisation. Combined with centered log-ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far. Two other variants are proposed for 1/ unbalanced batch x treatment designs that are commonly encountered in studies with small sample sizes, and for 2/ selection of discriminative variables amongst treatment groups to avoid overfitting in classification problems. These two variants have widened the scope of applicability of PLSDA-batch to different data settings.

Maintained by Yiwen (Eva) Wang. Last updated 5 months ago.

statisticalmethod dimensionreduction principalcomponent classification microbiome batcheffect normalization visualization

13 stars 5.37 score 18 scripts

stibu81

ibawds:Functions and Datasets for the Data Science Course at IBAW

A collection of useful functions and datasets for the Data Science Course at IBAW.

Maintained by Stefan Lanz. Last updated 11 days ago.

data-science-learning educational-resources

2 stars 5.24 score 8 scripts

cbg-ethz

clustNet:Network-Based Clustering

Network-based clustering using a Bayesian network mixture model with optional covariate adjustment.

Maintained by Fritz Bayer. Last updated 1 years ago.

bayesian-network bayesian-networks clustering dag genomics mixture-model network-clustering

7 stars 5.16 score 41 scripts

adefazio

classifierplots:Generates a Visualization of Classifier Performance as a Grid of Diagnostic Plots

Generates a visualization of binary classifier performance as a grid of diagnostic plots with just one function call. Includes ROC curves, prediction density, accuracy, precision, recall and calibration plots, all using ggplot2 for easy modification. Debug your binary classifiers faster and easier!

Maintained by Aaron Defazio. Last updated 4 years ago.

50 stars 5.08 score 16 scripts

jamesramsay5

TestGardener:Information Analysis for Test and Rating Scale Data

Develop, evaluate, and score multiple choice examinations, psychological scales, questionnaires, and similar types of data involving sequences of choices among one or more sets of answers. This version of the package should be considered as brand new. Almost all of the functions have been changed, including their argument list. See the file NEWS.Rd in the Inst folder for more information. Using the package does not require any formal statistical knowledge beyond what would be provided by a first course in statistics in a social science department. There the user would encounter the concept of probability and how it is used to model data and make decisions, and would become familiar with basic mathematical and statistical notation. Most of the output is in graphical form.

Maintained by James Ramsay. Last updated 1 years ago.

1 stars 2.70 score 5 scripts