proxyJK | R Documentation |
Perform a jackknife estimate of proxy curve fitting for time series analysis.
proxyJK(x, y, dx)
x |
x-axis values |
y |
y-axis values |
dx |
width of window to span in time |
Routine that improves on the Wilkinson and Ivany(2002) approach to climate time series modeling. The jackknife is used to estimate the 95 percent confidence bounds for the modeled estimates. dx should be chosen to be approximately half a cycle or more.
List:
OUT |
list( par, mid, ax, predmid,JKest, JKvar, PSTILDE ) |
omids |
output midpoints |
pmids |
values at output midpoints |
x |
input x |
y |
input y |
predy |
predicted y from spline fit |
See proxyA for a duplication of the Wilkinson codes.
Jonathan M. Lees<jonathan.lees@unc.edu>
Wang, T., Surge, D., and Lees, J. M., (2015) ClamR: A Statistical Evaluation of Isotopic and Temperature Records in Sclerochronologic Studies. Palaeogeography, Palaeoclimatology, Palaeoecology, doi:10.1016/j.palaeo.2015.07.008.
proxyA
## Not run:
########## this is for reading in data
######## fn = "/home/lees/DONNA/donna_viking_1.csv"
## fn = "donna_viking_1.csv"
######## C1 = scan(file=fn, what=list(mm="", o18=""), sep=",")
######## x = as.numeric(C1$mm)
######## y = as.numeric(C1$o18)
########x = x[!is.na(y)]
########y = y[!is.na(y)]
data(CLAM1)
x = CLAM1$x
y = CLAM1$y
dx = 3.392
gout = proxyJK(x, y, dx)
plotproxy1(x, y, gout)
par(mfrow=c(2,1))
plotproxy.error(x, y, gout, type = 1)
plotproxy.error(x, y, gout, type = 2)
par(mfrow=c(2,1))
plotproxy.error(x, y, gout, type = 2)
plotproxy.all2(gout, YAXstyle=1 )
## End(Not run)
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