Observed trajectory on a uniform time grid

This release assimilates a complete record of the observed state on a uniform grid, taken as noise-free. Every observed channel must be present at every time, the times must be strictly increasing and uniformly spaced, and the values must be finite; independent sensor error is refused rather than absorbed. observed_trajectory() constructs the observation object consumed throughout the package and enforces those requirements.

Usage

observed_trajectory(t, x, noise_free = TRUE, names = NULL)

Arguments

t

Numeric vector of observation times, strictly increasing and uniformly spaced.

x

Numeric matrix of observations with one row per time and at least one column, or a vector coerced to a single column.

noise_free

Logical; must be TRUE, since noisy observations are not supported in this version.

names

Optional character vector of unique, non-empty column names, one per observed channel.

Value

An object of class obs_traj: a list with the time vector t, the observation matrix x, the step dt, the observed dimension k and the flag noise_free.

Details

The noise-free restriction follows the method's current published scope: andreou2026cir Section 2.1 leaves noise-contaminated observations to future work, and its Discussion lists them as an open direction, so this is a limitation of the framework as published, not a modelling assumption added by the package.

See also

as_obs(), aci_filter()

Examples

observed_trajectory(t = seq(0, 1, by = 0.1),
                    x = matrix(rnorm(11), ncol = 1))
#> <obs_traj> k = 1, N+1 = 11, dt = 0.1, span [0, 1]