SEA: Superposed Epoch Analysis
In paleofire: Analysis of Charcoal Records from the Global Charcoal Database
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
The function performs a Superposed Epoch Analysis on a provided temporal serie.
The function uses pfCircular function for the computation of
the block bootstrap procedure. The function could be used on both dendrochronological
data and other data expressed in CE ages as well on paleoecological series expressed in BP.
Proxy data and ages must be spaced evenly but not necessarily using 1 yr time steps.
Usage
1
2
3
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6
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8
9
10
11
Arguments
x
data frame or matrix with ages and proxy values, younger ages on top.
y
events dates.
lag
lag time used for calculating the SEA.
b
A numeric giving block size, if NULL the optimal block size is given by: b= 2x(-1 /log(p)), where p is the lag one
autocorrelation coefficient of the serie (Adams, Mann & Ammann 2003).
conf
confidence intervals for the block bootstrap procedure.
nboot
number of bootstrap replicates.
center
logical, center each epoch by substracting values to each epoch's mean (default = FALSE).
normalize
logical, normalize each epoch by calculating Z-Score (default = FALSE, see Adams, Mann & Ammann 2003)
age
type of ages used in x[,1] either "CE" for Common Era or "BP" for Before Present.
Value
res
A "pfCircular" object with estimated confidence intervals.
Author(s)
O. Blarquez
See Also
Examples
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## Not run:
## Generate some fake data
set.seed(1)
n <- 100 # number of data points
t <- seq(0,4*pi,,100)
a <- 3
b <- 2
c.unif <- runif(n)
amp <- 4
# generate data and calculate "y"
set.seed(1)
y1 <- a*sin(b*t)+c.unif*amp # add uniform error
# SEA applied to fake dendrochronological data in CE
plot(rev(seq(1901,2000,1)), y1, t="l", ylim=range(y1)*c(1.2))
y=c(1923,1948,1972,1995)
points(y,rep(0,length(y)))
x=data.frame(rev(seq(1901,2000,1)),value=y1)
lag=10
#Perform SEA
res=SEA(x, y, lag, b = NULL, conf = c(0.05, 0.95), nboot = 1000, age="CE")
plot(res,xlim=c(-10,10),xlab="lag",ylab="Composite mean")
# SEA applied to fake paleoecological data in BP
plot(seq(-50,49,1), y1, t="l", ylim=range(y1)*c(1.2),xlim=c(50,-50))
y=1950-c(1923,1948,1972,1995)
points(y,rep(0,length(y)))
x=data.frame(seq(-50,49,1),value=y1)
# Perform SEA
res=SEA(x, y, lag, b = NULL, conf = c(0.05, 0.95), nboot = 1000, age="BP")
plot(res,xlim=c(-10,10),xlab="lag",ylab="Composite mean")
## End(Not run)
Example output
Loading required package: GCD
This is paleofire v1.2.4 | GCD v4.0.7
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paleofire documentation built on Jan. 11, 2020, 9:44 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Author(s) See Also Examples
Description
The function performs a Superposed Epoch Analysis on a provided temporal serie. The function uses pfCircular function for the computation of the block bootstrap procedure. The function could be used on both dendrochronological data and other data expressed in CE ages as well on paleoecological series expressed in BP. Proxy data and ages must be spaced evenly but not necessarily using 1 yr time steps.
Usage
1 2 3 4 5 6 7 8 9 10 11 |
Arguments
x |
data frame or matrix with ages and proxy values, younger ages on top. |
y |
events dates. |
lag |
lag time used for calculating the SEA. |
b |
A numeric giving block size, if NULL the optimal block size is given by: b= 2x(-1 /log(p)), where p is the lag one autocorrelation coefficient of the serie (Adams, Mann & Ammann 2003). |
conf |
confidence intervals for the block bootstrap procedure. |
nboot |
number of bootstrap replicates. |
center |
logical, center each epoch by substracting values to each epoch's mean (default = FALSE). |
normalize |
logical, normalize each epoch by calculating Z-Score (default = FALSE, see Adams, Mann & Ammann 2003) |
age |
type of ages used in x[,1] either "CE" for Common Era or "BP" for Before Present. |
Value
res |
A "pfCircular" object with estimated confidence intervals. |
Author(s)
O. Blarquez
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ## Not run:
## Generate some fake data
set.seed(1)
n <- 100 # number of data points
t <- seq(0,4*pi,,100)
a <- 3
b <- 2
c.unif <- runif(n)
amp <- 4
# generate data and calculate "y"
set.seed(1)
y1 <- a*sin(b*t)+c.unif*amp # add uniform error
# SEA applied to fake dendrochronological data in CE
plot(rev(seq(1901,2000,1)), y1, t="l", ylim=range(y1)*c(1.2))
y=c(1923,1948,1972,1995)
points(y,rep(0,length(y)))
x=data.frame(rev(seq(1901,2000,1)),value=y1)
lag=10
#Perform SEA
res=SEA(x, y, lag, b = NULL, conf = c(0.05, 0.95), nboot = 1000, age="CE")
plot(res,xlim=c(-10,10),xlab="lag",ylab="Composite mean")
# SEA applied to fake paleoecological data in BP
plot(seq(-50,49,1), y1, t="l", ylim=range(y1)*c(1.2),xlim=c(50,-50))
y=1950-c(1923,1948,1972,1995)
points(y,rep(0,length(y)))
x=data.frame(seq(-50,49,1),value=y1)
# Perform SEA
res=SEA(x, y, lag, b = NULL, conf = c(0.05, 0.95), nboot = 1000, age="BP")
plot(res,xlim=c(-10,10),xlab="lag",ylab="Composite mean")
## End(Not run)
|
Example output
Loading required package: GCD
This is paleofire v1.2.4 | GCD v4.0.7
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