Fit a non-homogeneous Poisson process model to the exceedances of a time series.

Fit a non-homogeneous Poisson process model to the exceedances of a time series.

Usage

fit_nhpp(x, tau, ...)

Arguments

x

A time series

tau

A vector of changepoints

...

currently ignored

Value

An nhpp object, which inherits from mod_cpt.

Details

Any time series can be modeled as a non-homogeneous Poisson process of the locations of the exceedances of a threshold in the series. This function uses the BMDL criteria to determine the best fit parameters for each region defined by the changepoint set tau.

See also

Other model-fitting: fit_arima(), fit_lmshift(), fit_meanshift(), fit_meanvar(), model_args(), model_name(), new_fun_cpt(), whomademe()

Examples

# Fit an NHPP model using the mean as a threshold
fit_nhpp(DataCPSim, tau = 826)
#> ℹ Model: A nhpp  model with 2 region(s).
#> → Each region has 2 parameter(s).
#> → The model has 1 global parameter(s).

# Fit an NHPP model using other thresholds
fit_nhpp(DataCPSim, tau = 826, threshold = 20)
#> ℹ Model: A nhpp  model with 2 region(s).
#> → Each region has 2 parameter(s).
#> → The model has 1 global parameter(s).
fit_nhpp(DataCPSim, tau = 826, threshold = 200)
#> ℹ Model: A nhpp  model with 2 region(s).
#> → Each region has 2 parameter(s).
#> → The model has 1 global parameter(s).

# Fit an NHPP model using changepoints determined by PELT
fit_nhpp(DataCPSim, tau = changepoints(segment(DataCPSim, method = "pelt")))
#> ℹ Model: A nhpp  model with 4 region(s).
#> → Each region has 2 parameter(s).
#> → The model has 1 global parameter(s).