Struct SmoothingKernelIntensity

pub struct SmoothingKernelIntensity<K: RegKernel> { /* private fields */ }

Estimate the intensity function of an event sequence under a variable Poisson model using a kernel smoother (see A kernel method for smoothing point process data by P. Diggle). The regressor is given by $$ \hat\lambda(t) = e_h(t)^{-1} \sum_i K_h(t - t_i) $$ where $e_h(t) = \int_0^T K_h(t - u)\, du$ is an edge-correction term.

Implementations

impl<K> SmoothingKernelIntensity<K>

where K: RegKernelMass,

pub fn fit<T>(self, evts: Vec<T>) -> Self

where T: Into<Array1<f64>>,

pub fn predict(&self, x0: f64, tmax: f64) -> f64

impl SmoothingKernelIntensity<NearestNeighborKernel>

pub fn new(bandwidth: f64) -> Self