Function reference
Main function
All implementation of fastcpd is unified into one single function fastcpd()
.
-
fastcpd()
- Find change points efficiently
Time series
fastcpd.ts()
and fastcpd_ts()
are the main functions for time series data.
-
fastcpd.ar()
fastcpd_ar()
- Find change points efficiently in AR(p) models
-
fastcpd.arima()
fastcpd_arima()
- Find change points efficiently in ARIMA(p, d, q) models
-
fastcpd.arma()
fastcpd_arma()
- Find change points efficiently in ARMA(p, q) models
-
fastcpd.garch()
fastcpd_garch()
- Find change points efficiently in GARCH(p, q) models
-
fastcpd.ma()
fastcpd_ma()
- Find change points efficiently in MA(q) models
-
fastcpd.ts()
fastcpd_ts()
- Find change points efficiently in time series data
-
fastcpd.var()
fastcpd_var()
- Find change points efficiently in VAR(p) models
Unlabeled data
Used for data without response variables, for example, mean change and variance change.
-
fastcpd.mean()
fastcpd_mean()
- Find change points efficiently in mean change models
-
fastcpd.variance()
fastcpd_variance()
- Find change points efficiently in variance change models
-
fastcpd.meanvariance()
fastcpd_meanvariance()
fastcpd.mv()
fastcpd_mv()
- Find change points efficiently in variance change models
-
fastcpd.binomial()
fastcpd_binomial()
- Find change points efficiently in logistic regression models
-
fastcpd.lasso()
fastcpd_lasso()
- Find change points efficiently in penalized linear regression models
-
fastcpd.lm()
fastcpd_lm()
- Find change points efficiently in linear regression models
-
fastcpd.poisson()
fastcpd_poisson()
- Find change points efficiently in Poisson regression models
-
plot(<fastcpd>)
plot(<fastcpd>,<missing>)
- Plot the data and the change points for a
fastcpd
object
-
print(<fastcpd>)
print(<fastcpd>)
- Print the call and the change points for a
fastcpd
object
-
show(<fastcpd>)
show(<fastcpd>)
- Show the available methods for a
fastcpd
object
-
summary(<fastcpd>)
summary(<fastcpd>)
- Show the summary of a
fastcpd
object
Data
fastcpd comes with a selection of built-in datasets that are used in examples to illustrate various change point detection challenges.
-
bitcoin
- Bitcoin Market Price (USD)
-
occupancy
- Occupancy Detection Data Set
-
transcriptome
- Transcription Profiling of 57 Human Bladder Carcinoma Samples
-
uk_seatbelts
- UK Seatbelts Data
-
well_log
- Well-log Dataset from Numerical Bayesian Methods Applied to Signal Processing
Main class
The results of fastcpd()
will be stored in the class fastcpd
with accompanied several utility functions.
-
fastcpd-class
- An S4 class to store the output created with fastcpd