unscentedKalmanFilter: Unscented Kalman Filter

In piotrek-orlowski/ukfRcpp: R and C++ Unscented Kalman Filter

Description

This function accepts pointers to compiled c++ evaluator functions for the observation equations and the transition equations, plus data and parameters, and evaluates the UKF.

Arguments

dataMat	matrix containing observed data, by-column
initState	initial state vector values
initProcCov	initial variance-covariance matrix of the state vector
modelParams	list of model parameter objects, compatible with your predictState and evaluateState functions, and with the specification of the ukfClass
predict_Xptr	XPtr to predictState function which handles your one-step head prediction of the state variable, given current values.
evaluate_XPtr	XPtr to evaluateState function which calculates the values of the measurement equation given values of the state.
control_XPtr	XPtr to stateController function which handles pathological state cases after the filtering step (e.g. when using a Gaussian filter on strictly positive variables, which turn negative after the filtering step, it is useful to set them to a small value)

Value

List with the following fields: estimState (T+1) x N matrix of filtered states, with the initial state vector in the first row; stateCovCube 3-dimensional array of posterior state variance-covariance matrices, N x N x T; logL vector of Gaussian likelihood values, see e.g. "Time Series Analysis" by J.D. Hamilton, predMat T x M matrix of predictions of observations at time t given observations at time t-1, fitMat T x M matrix of observation equations evaluated at filtered state values.

piotrek-orlowski/ukfRcpp documentation built on July 21, 2020, 11:51 a.m.