TPMplt (version 0.1.6)

KFprocess: Enhanced Kalman filter to reduce the noise of raw data

Description

Kalman filter reducing the noise in raw data if it is necessary.

Usage

KFprocess(x, manual = NULL, ...)

Value

A data frame with the identical shape as input data, but with the smoothed stress values.

Arguments

x

A data frame with VBTree style. Pay attention, all factors in column names should be separated by "-" symbol, and factors for temperatures and strain rates should be saved in pure numeric style.

manual

An integer vector with the length of 3 where the 1st element denotes the layer for Stress and Strain, the 2nd and 3rd elements represent the levels for Strain and Stress, respectively. The default setting is NULL, which can call the function lyIDdetector for automatic completion.

...

The arguments dV and dW passed on to dlmModPoly in the function dlmSmooth.

See Also

VBTree, dlmModPoly, dlmSmooth

Examples

# \donttest{
# raw data without smoothing:
SSplots(TPMdata, 2, mfrow=c(2, 2))

# Smoothing to reduce the noise:
KFdt <-KFprocess(TPMdata, dV = 0.3, dW = 0.006)
SSplots(KFdt, 2, mfrow=c(2, 2))
# }