Package: knnwtsim 1.1.0.9000

Matthew Trupiano

knnwtsim: K Nearest Neighbor Forecasting with a Tailored Similarity Metric

Functions to implement K Nearest Neighbor forecasting using a weighted similarity metric tailored to the problem of forecasting univariate time series where recent observations, seasonal patterns, and exogenous predictors are all relevant in predicting future observations of the series in question. For more information on the formulation of this similarity metric please see Trupiano (2021) <arxiv:2112.06266>.

Authors:Matthew Trupiano

knnwtsim_1.1.0.9000.tar.gz
knnwtsim_1.1.0.9000.zip(r-4.7-any)knnwtsim_1.1.0.9000.zip(r-4.6-any)knnwtsim_1.1.0.9000.zip(r-4.5-any)
knnwtsim_1.1.0.9000.tgz(r-4.6-any)knnwtsim_1.1.0.9000.tgz(r-4.5-any)
knnwtsim_1.1.0.9000.tar.gz(r-4.7-any)knnwtsim_1.1.0.9000.tar.gz(r-4.6-any)
knnwtsim_1.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
knnwtsim/json (API)

# Install 'knnwtsim' in R:
install.packages('knnwtsim', repos = c('https://mtrupiano1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mtrupiano1/knnwtsim/issues

Datasets:

On CRAN:

Conda:

forecastingknn-regressionmachine-learningtime-series

2.70 score 1 stars 2 scripts 259 downloads 10 exports 0 dependencies

Last updated from:90ea40721d. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK95
source / vignettesOK145
linux-releaseOK88
macos-releaseOK135
macos-oldrelOK148
windows-develOK60
windows-releaseOK52
windows-oldrelOK56
wasm-releaseOK72

Exports:knn.forecastknn.forecast.boot.intervalsknn.forecast.randomsearch.tuningNNregSeasonalAbsDissimilaritySpMatrixCalcStMatrixCalcSwMatrixCalcSxMatrixCalcTempAbsDissimilarity

Dependencies: