eAsm {astrochron} | R Documentation |
Evolutive Average Spectral Misfit
Description
Calculate Evolutive Average Spectral Misfit with Monte Carlo spectra simulations, as updated in Meyers et al. (2012).
Usage
eAsm(spec,siglevel=0.9,target,fper=NULL,rayleigh,nyquist,sedmin=1,sedmax=5,
numsed=50,linLog=1,iter=100000,ydir=1,palette=2,output=4,genplot=F)
Arguments
spec |
Time-frequency spectral results to evaluate. Must have the following format: column 1=frequency; remaining columns (2 to n)=probability; titles for columns 2 to n must be the location (depth or height). Note that this format is ouput by function eha. |
siglevel |
Threshold level for filtering peaks. |
target |
A vector of astronomical frequencies to evaluate (1/ka). These must be in order of increasing frequency (e.g., e1,e2,e3,o1,o2,p1,p2). Maximum allowed is 50 frequencies. |
fper |
A vector of uncertainties on each target frequency (1/ka). Values should be from 0-1, representing uncertainty as a percent of each target frequency. The order of the uncertainties must follow that of the target vector. By default, no uncertainty is assigned. |
rayleigh |
Rayleigh frequency (cycles/m). |
nyquist |
Nyquist frequency (cycles/m). |
sedmin |
Minimum sedimentation rate for investigation (cm/ka). |
sedmax |
Maximum sedimentation rate for investigation (cm/ka). |
numsed |
Number of sedimentation rates to investigate in ASM optimization grid. Maximum allowed is 500. |
linLog |
Use linear or logarithmic scaling for sedimentation rate grid spacing? (0=linear, 1=log) |
iter |
Number of Monte Carlo simulations for significance testing. Maximum allowed is 100,000. |
ydir |
Direction for y-axis in plots (depth or height). -1 = values increase downwards (slower plotting!), 1 = values increase upwards. |
palette |
What color palette would you like to use? (1) rainbow, (2) viridis |
output |
Return output as a new data frame? (0 = nothing, 1 = Ho-SL, 2 = ASM, 3 = # astronomical terms, 4 = everything) |
genplot |
Generate summary plots? (T or F) |
Details
Please see function asm for details.
References
S.R. Meyers and B.B. Sageman, 2007, Quantification of Deep-Time Orbital Forcing by Average Spectral Misfit: American Journal of Science, v. 307, p. 773-792.
S.R. Meyers, 2012, Seeing Red in Cyclic Stratigraphy: Spectral Noise Estimation for Astrochronology: Paleoceanography, 27, PA3228, doi:10.1029/2012PA002307.
S.R. Meyers, B.B. Sageman and M.A. Arthur, 2012, Obliquity forcing of organic matter accumulation during Oceanic Anoxic Event 2: Paleoceanography, 27, PA3212, doi:10.1029/2012PA002286.
See Also
asm
, eAsmTrack
, eha
, testPrecession
, timeOpt
, and timeOptSim
Examples
## Not run:
# use modelA as an example
data(modelA)
# interpolate to even sampling interval
modelAInterp=linterp(modelA)
# perform EHA analysis, save harmonic F-test confidence level results to 'spec'
spec=eha(modelAInterp,win=8,step=2,pad=1000,output=4)
# perform Evolutive Average Spectral Misfit analysis, save results to 'res'
res=eAsm(spec,target=c(1/405.47,1/126.98,1/96.91,1/37.66,1/22.42,1/18.33),rayleigh=0.1245274,
nyquist=6.66597,sedmin=0.5,sedmax=3,numsed=100,siglevel=0.8,iter=10000,output=4)
# identify minimum Ho-SL in each record and plot
pl(1)
eAsmTrack(res[1],threshold=0.05)
# extract Ho-SL result at 18.23 m
HoSL18.23=extract(res[1],get=18.23,pl=1)
# extract ASM result at 18.23 m
asm18.23=extract(res[2],get=18.23,pl=0)
## End(Not run)