Package: predkmeans 0.1.1
predkmeans: Covariate Adaptive Clustering
Implements the predictive k-means method for clustering observations, using a mixture of experts model to allow covariates to influence cluster centers. Motivated by air pollution epidemiology settings, where cluster membership needs to be predicted across space. Includes functions for predicting cluster membership using spatial splines and principal component analysis (PCA) scores using either multinomial logistic regression or support vector machines (SVMs). For method details see Keller et al. (2017) <doi:10.1214/16-AOAS992>.
Authors:
predkmeans_0.1.1.tar.gz
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predkmeans_0.1.1.tgz(r-4.4-x86_64)predkmeans_0.1.1.tgz(r-4.4-arm64)predkmeans_0.1.1.tgz(r-4.3-x86_64)predkmeans_0.1.1.tgz(r-4.3-arm64)
predkmeans_0.1.1.tar.gz(r-4.5-noble)predkmeans_0.1.1.tar.gz(r-4.4-noble)
predkmeans_0.1.1.tgz(r-4.4-emscripten)predkmeans_0.1.1.tgz(r-4.3-emscripten)
predkmeans.pdf |predkmeans.html✨
predkmeans/json (API)
NEWS
| # Install 'predkmeans' in R: |
| install.packages('predkmeans', repos = c('https://kpkeller.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kpkeller/predkmeans/issues
Last updated 5 years agofrom:4a47447a64. Checks:OK: 7 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 26 2024 |
| R-4.5-win-x86_64 | NOTE | Oct 26 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 26 2024 |
| R-4.4-win-x86_64 | OK | Oct 26 2024 |
| R-4.4-mac-x86_64 | OK | Oct 26 2024 |
| R-4.4-mac-aarch64 | OK | Oct 26 2024 |
| R-4.3-win-x86_64 | OK | Oct 26 2024 |
| R-4.3-mac-x86_64 | OK | Oct 26 2024 |
| R-4.3-mac-aarch64 | OK | Oct 26 2024 |
Exports:assignClustercreateCVgroupscreatePCAmodelmatrixcreateTPRSmodelmatrixmlogitpredictionMetricspredictMixExppredictMLpredictSVMpredkmeanspredkmeansCVestpredkmeansCVpred
Dependencies:classdigeste1071genericslatticeMASSMatrixmaxLikmgcvmiscToolsnlmeproxyRcppRcppArmadillosandwichzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Covariate Adaptive Clustering | predkmeans-package |
| Make Cluster Assignments | assignCluster |
| Creating k-fold Cross-Validation Groups | createCVgroups |
| Create Principal Component Analysis (PCA) scores matrix | createPCAmodelmatrix |
| Create matrix of Thin-Plate Regression Splines (TPRS) | createTPRSmodelmatrix |
| Multinomial Logistic Regression | mlogit |
| Measures of Prediction Performance | predictionMetrics |
| Prediction of Cluster Membership | predictMixExp predictMixExp.predkmeans predictML predictML.predkmeans predictSVM predictSVM.predkmeans |
| Predictive K-means Clustering | predkmeans |
| Cross-validation of Predictive K-means Clustering | predkmeansCVest predkmeansCVpred |
| Re-order cluster labels | relevel.predkmeans |
