Chan_update: Processing a new data point for the 'Chan' class
In ocd: High-Dimensional Multiscale Online Changepoint Detection
Description
Usage
Arguments
Value
References
Description
This function implements the getData function to
perform the online changepoint detection for the 'Chan' class.
Usage
1
Chan_update(x_new, X_recent, CUSUM, p0, w, lambda)
Arguments
x_new
a new data point
X_recent
matrix of w most recent observations
CUSUM
tail partial sums of different lengths to be tracked online
p0
sparsity parameter
w
window parameter
lambda
a tuning parameter for the 'Chan' method
Value
a list of
stat: test statistic for the 'Chan' class.
X_recent: the updated X_recent matrix
CUSUM: the updated CUSUM matrix
References
Chan, H. P. (2017) Optimal sequential detection in multi-stream data.
Ann. Statist., 45, 2736–2763.
ocd documentation built on Oct. 23, 2020, 5:56 p.m.
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Description Usage Arguments Value References
Description
This function implements the getData function to
perform the online changepoint detection for the 'Chan' class.
Usage
1 | Chan_update(x_new, X_recent, CUSUM, p0, w, lambda)
|
Arguments
x_new |
a new data point |
X_recent |
matrix of |
CUSUM |
tail partial sums of different lengths to be tracked online |
p0 |
sparsity parameter |
w |
window parameter |
lambda |
a tuning parameter for the 'Chan' method |
Value
a list of
stat: test statistic for the 'Chan' class.
X_recent: the updated X_recent matrix
CUSUM: the updated CUSUM matrix
References
Chan, H. P. (2017) Optimal sequential detection in multi-stream data. Ann. Statist., 45, 2736–2763.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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