opart_poisson: compute the optimal changepoint model for a vector of...
In opart: Optimal Partitioning
Description
Usage
Arguments
Value
Examples
View source: R/opart_poission.R
Description
compute the optimal changepoint model for a vector of real-valued data
and a non-negative real-valued penalty,
given the poisson loss (to minimize) / log likelihood (to maximize)
Usage
1
opart_poisson(data, penalty)
Arguments
data
A list of numbers for which the changepoint model is to be computed
penalty
A non-negative real number indicating penalty parameter
Value
An error status code with a pointer to the optimal cost values and a pointer to the optimal segment ends
Examples
1
2
sample_data <- rpois(100, 10.5)
opart::opart_poisson(data=sample_data, penalty=1)
opart documentation built on Sept. 4, 2019, 5:03 p.m.
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Description Usage Arguments Value Examples
View source: R/opart_poission.R
Description
compute the optimal changepoint model for a vector of real-valued data and a non-negative real-valued penalty, given the poisson loss (to minimize) / log likelihood (to maximize)
Usage
1 | opart_poisson(data, penalty)
|
Arguments
data |
A list of numbers for which the changepoint model is to be computed |
penalty |
A non-negative real number indicating penalty parameter |
Value
An error status code with a pointer to the optimal cost values and a pointer to the optimal segment ends
Examples
1 2 | sample_data <- rpois(100, 10.5)
opart::opart_poisson(data=sample_data, penalty=1)
|
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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