Introduction to EpidigiR: Epidemiological Analysis and Visualization | Setup | Datasets | Examples | Summary Statistics | SIR Epidemic Model | Spatial map | Logistic Model | Random Forest with Clinical Data | Global Health Burden (DALY) | SNP Association | Age Standardization | Machine-learning-logistic | Survival Analysis | NLP-keyword Extraction | K-means Clustering | SVM-Modelling | Diagnostic Tests | boxplot-visualization | Scatter-visualization | Conclusion | License
Package: EpidigiR 0.1.2
Esther Atsabina Wanjala
EpidigiR: Digital Epidemiological Analysis and Visualization Tools
Integrates methods for epidemiological analysis, modeling, and visualization, including functions for summary statistics, SIR (Susceptible-Infectious-Recovered) modeling, DALY (Disability-Adjusted Life Years) estimation, age standardization, diagnostic test evaluation, NLP (Natural Language Processing) keyword extraction, clinical trial power analysis, survival analysis, SNP (Single Nucleotide Polymorphism) association, and machine learning methods such as logistic regression, k-means clustering, Random Forest, and Support Vector Machine (SVM). Includes datasets for prevalence estimation, SIR modeling, genomic analysis, clinical trials, DALY, diagnostic tests, and survival analysis. Methods are based on Gelman et al. (2013) <doi:10.1201/b16018> and Wickham et al. (2019, ISBN:9781492052040>.
Authors:
EpidigiR_0.1.2.tar.gz
EpidigiR_0.1.2.tar.gz(r-4.7-any)EpidigiR_0.1.2.tar.gz(r-4.6-any)
EpidigiR_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EpidigiR/json (API)
| # Install 'EpidigiR' in R: |
| install.packages('EpidigiR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- clinical_data - Clinical Trials Data for Epidemiological Analysis
- daly_data - DALY Data for Global Health Burden
- diagnostic_data - Diagnostic Test Data for Evaluation
- epi_prevalence - Disease Prevalence Data by Region and Age Group
- geno_data - Genomic SNP-Case Data
- ml_data - Machine Learning Data for Disease Risk Prediction
- nlp_data - NLP Data for Epidemiological Text Analysis
- sir_data - SIR Model Simulation Data
- survey_data - Survey Data for Age Standardization
- survival_data - Survival Analysis Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:5684241436. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 187 | ||
| source / vignettes | OK | 223 | ||
| linux-release-x86_64 | OK | 183 | ||
| wasm-release | OK | 188 |
Exports:epi_analyzeepi_modelepi_visualize
Dependencies:BHcaretclasscliclockcodetoolscpp11data.tabledeSolvediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2glmnetglobalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmeNLPnnetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartS7scalesshapeslamspsparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetmtzdbutf8vctrsviridisLitewithrxml2
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Clinical Trials Data for Epidemiological Analysis | clinical_data |
| DALY Data for Global Health Burden | daly_data |
| Diagnostic Test Data for Evaluation | diagnostic_data |
| Performs summary statistics, SIR modeling, DALY calculation, age standardization, diagnostic test evaluation, or NLP keyword extraction. | epi_analyze |
| Unified Epidemiological Modeling | epi_model |
| Disease Prevalence Data by Region and Age Group | epi_prevalence |
| Flexible Epidemiological Visualization | epi_visualize |
| Genomic SNP-Case Data | geno_data |
| Machine Learning Data for Disease Risk Prediction | ml_data |
| NLP Data for Epidemiological Text Analysis | nlp_data |
| SIR Model Simulation Data | sir_data |
| Survey Data for Age Standardization | survey_data |
| Survival Analysis Data | survival_data |