memCoef: memCoef

In WilliamCooper/Ranadu: Functions for use with RAF aircraft data files

Description

Calculates the Burg-algorithm coefficients for MEM spectral estimation

Usage

memCoef(.data, .poles = NA)

Arguments

.data	Numeric vector of data points. Often this should first have mean and trend removed, e.g., using detrend() provided here, but that should be performed using a data.frame that includes a 'Time' variable as the first variable. The numeric vector .data then can be the output from that function.
.poles	Number of poles to use in the calculation. A small number produces a smooth spectrum, which a large number is needed for high-resolution features. A reasonable number (and the default) is 5% of the length of the .data vector. Values comparable to the length of the .data vector can take an awkwardly long time.

Details

The resulting coefficients can be used as input to memEstimate to calculate the variance spectrum. The full output list as returned from this function should be provided to memEstimate.

Value

A list with these components: [[1]] .poles As used in the calculation [[2]] cf0 The mean-square discrepancy [[3]] cf Numeric vector of coefficients, length=.poles

Author(s)

William Cooper

References

p. 568, Numerical Recipes in C, Second Edition, Press et al. (but here coded independently in R, following the algorithm specified there)

Examples

S <- memCoef(RAFdata[, 'TASX'])

WilliamCooper/Ranadu documentation built on July 10, 2019, 12:40 a.m.