Package: anomalous 0.0.4.2

anomalous: Anomaly Detection using the CAPA and PELT Algorithms

Implimentations of the univariate CAPA <doi:10.1002/sam.11586> and PELT <doi:10.1080/01621459.2012.737745> algotithms along with various cost functions for different distributions and models. The modular design, using R6 classes, favour ease of extension (for example user written cost functions) over the performance of other implimentations (e.g. <doi:10.32614/CRAN.package.changepoint>, <doi:10.32614/CRAN.package.anomaly>).

Authors:Paul Smith [aut, cre]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
anomalous/json (API)

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

Bug tracker:https://github.com/waternumbers/anomalous/issues

Pkgdown/docs site:https://waternumbers.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • Lai2005fig4 - Normalized glioblastoma profile for an excerpt of chromosome 7, the EGFR locus.
  • machinetemp - Machine temperature data.
  • sim.data - Simulated data.
  • wind - Ireland wind data, 1961-1978
  • wind.loc - Ireland wind data, 1961-1978

On CRAN:

Conda:

cpp

3.91 score 18 scripts 19 exports 2 dependencies

Last updated from:fd9c8daf67. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK227
linux-devel-x86_64OK240
source / vignettesOK201
linux-release-arm64OK220
linux-release-x86_64OK225
macos-release-arm64OK161
macos-release-x86_64OK499
macos-oldrel-arm64OK159
macos-oldrel-x86_64OK368
windows-develOK263
windows-releaseOK289
windows-oldrelOK233
wasm-releaseOK110

Exports:capacategoricalCostcollective_anomaliescropsgaussMeangaussMeanVargaussRegMeangaussRegMeanVargaussRegVargaussVarladCostlocalRegCostmultinomialCostparampartitionpeltpoint_anomaliespoisCostrankCost

Dependencies:R6Rcpp

Creating Cost Functions
Rendered fromcreating_cost_functions.Rmdusingknitr::knitr

Last update: 2024-12-13
Started: 2024-12-13

Using anomalous
Context | Using CAPA for anomalies | Using PELT for change points | CROPS for varaible penalties
Rendered fromanomalous.Rmdusingknitr::knitr

Last update: 2024-12-13
Started: 2023-06-06

Categorical Cost Calculations
No Anomaly (Baseline) | Anomaly
Rendered fromcategorical.Rmdusingknitr::knitr

Last update: 2024-09-09
Started: 2024-09-09

Univariate Gaussian Cost Calculations
No Anomaly (Baseline) | Collective Anomalies | Anomaly in Mean and Variance | Anomaly in Mean | Anomaly in Variance | Point anomaly | [C_{P_{M}}\left(y_{t}\left| m_{t},s_{t},\hat{\mu}{k}\right.\right) -C{B}\left(y_{t}\left| m_{t},s_{t}\right.\right) | [C_{P_{V}}\left(y_{t}\left| m_{t},s_{t},\hat{\sigma}{k}\right.\right) -C{B}\left(y_{t}\left| m_{t},s_{t}\right.\right) | Relating this to the background cost we see that point anomalies may be accepted in the capa search when[f\left(z_{t},\gamma,\beta\right) =C_{P_{V}}\left(y_{t}\left| m_{t},s_{t},\hat{\sigma}{k},\gamma\right.\right) -C{B}\left(y_{t}\left| m_{t},s_{t}\right.\right)
Rendered fromunivariate_gaussian.Rmdusingknitr::knitr

Last update: 2024-09-09
Started: 2024-09-09

Univariate Poisson Cost Calculations
No Anomaly (Baseline) | Anomaly in Rate
Rendered fromunivariate_poisson.Rmdusingknitr::knitr

Last update: 2024-09-09
Started: 2024-09-09

Quantile Cost Calculations
Quantile regression | Baseline: No Anomaly | Collective anomaly | Point Anomaly
Rendered fromquantile.Rmdusingknitr::knitr

Last update: 2023-12-20
Started: 2023-12-20

Regression Cost Calculations
Linear regression | Sufficent statistics | Baseline: No Anomaly | Collective Anomalies | Anomaly in Regression parameters | Anomaly in Variance | Anomaly in regression parameters and variance | Since[\sum_{t \in T_{k}} \left( \hat{\mathbf{y}}{t} - \mathbf{X}{t} \theta_{k}\right)^{\prime} \mathbf{S}{t}^{-1} \left( \hat{\mathbf{y}}{t} - \mathbf{X}{t} \theta{k}\right) | Point anomaly
Rendered fromregression_cost_calcs.Rmdusingknitr::knitr

Last update: 2023-12-20
Started: 2023-12-20

Replicate Cost Calculations
Univariate Gaussian | Anomaly in mean and varinace | Anomaly in Mean | Anomaly in Variance | No Anomaly (Baseline) | Point anomaly
Rendered fromreplicate_cost_calcs.Rmdusingknitr::knitr

Last update: 2023-12-20
Started: 2023-12-20

CROPS with anomalies
Framework | CROPS | Point anomalies
Rendered fromcrops.Rmdusingknitr::knitr

Last update: 2023-10-17
Started: 2023-10-17