fit_polynomial_sde: Polynomial based SDEs Estimation

In citiususc/voila: Variational Inference for Langevin Equations

Description

Polynomial based SDEs Estimation

Usage

fit_polynomial_sde(timeSeries, samplingPeriod = NULL, timeTs = NULL,
  nDrift = 1, nDiff = 1, direction = "both")

Arguments

timeSeries	A univariate vector representing the time series
samplingPeriod	The sampling period of the time series
timeTs	A vector with the occurrence time of each sample of the time series. Can be used as an alternative to samplingPeriod.
nDrift, nDiff	Maximum order of the polynomial used to fit the drift/diffusion term.
direction	The mode of stepwise search, can be one of "both", "backward", or "forward". See step.

Value

A list with two poly_sde objects representing the estimates for the drift and the diffusion terms. The poly_sde objects can be used with predict to get numerical estimates of the drift/diffusion functions.

citiususc/voila documentation built on May 13, 2019, 7:30 p.m.