fitPWRFisher {samurais} | R Documentation |
fitPWRFisher implements an optimized dynamic programming algorithm to fit a PWR model.
Description
fitPWRFisher is used to fit a Piecewise Regression (PWR) model by maximum-likelihood via an optimized dynamic programming algorithm. The estimation performed by the dynamic programming algorithm provides an optimal segmentation of the time series.
Usage
fitPWRFisher(X, Y, K, p = 3)
Arguments
X |
Numeric vector of length m representing the covariates/inputs
|
Y |
Numeric vector of length m representing the observed
response/output |
K |
The number of regimes/segments (PWR components). |
p |
Optional. The order of the polynomial regression. By default, |
Details
fitPWRFisher function implements an optimized dynamic programming
algorithm of the PWR model. This function starts with the calculation of
the "cost matrix" then it estimates the transition points given K
the
number of regimes thanks to the method computeDynamicProgram
(method of
the class ParamPWR).
Value
fitPWRFisher returns an object of class ModelPWR.
See Also
Examples
data(univtoydataset)
pwr <- fitPWRFisher(univtoydataset$x, univtoydataset$y, K = 5, p = 1)
pwr$summary()
pwr$plot()