R: Deconvolution of a single jump / isolated peak

deconvolve {lowpassFilter}

R Documentation

Deconvolution of a single jump / isolated peak

Description

For developers only; computes the deconvolution of a single jump or an isolated peak assuming that the observations are lowpass filtered. More details are given in (Pein et al., 2018).

Usage

.deconvolveJump(grid, observations, time, leftValue, rightValue,
                typeFilter, inputFilter, covariances) 
.deconvolvePeak(gridLeft, gridRight, observations, time, leftValue, rightValue,
                typeFilter, inputFilter, covariances, tolerance)

Arguments

`grid`, `gridLeft`, `gridRight`	numeric vectors giving the potential time points of the single jump, of the left and right jump points of the peak, respectively
`observations`	a numeric vector giving the observed data
`time`	a numeric vector of length `length(observations)` giving the time points at which the `observations` are observed
`leftValue`, `rightValue`	single numerics giving the value (conductance level) before and after the jump / peak, respectively
`typeFilter`, `inputFilter`	a description of the assumed lowpass filter, usually computed by `lowpassFilter`
`covariances`	a numeric vector giving the (regularized) covariances of the observations
`tolerance`	a single numeric giving a tolerance for the decision whether the left jump point is smaller than the right jump point

Value

For .deconvolveJump a single numeric giving the jump point. For .deconvolvePeak a list containing the entries left, right and value giving the left and right jump point and the value of the peak, respectively.

References