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Last data update: 2014.03.03 |
Median polish trendDescriptionDirect method to remove trend of spatio - temporal data througth median polish. UsageremovetrendMPst(MPST,eps=0.01, maxiter=10L) Arguments
DetailsRobust method introduced for Cressie(1993) and enhanced by Berke(2001) to remove trend of a space - time process with data ≤ft{y(mathbf{s}_{abc},t), a=1,...,U; b=1,...,V; c=1,...,W, t=1,...,n ight} Y(mathbf{s}_{abc},t)= μ_{y}(mathbf{s}_{abc},t) + δ _{abct} where μ _{y}(mathbf{s}_{abc},t)= μ +α _{a} + β _{b} + ξ _{c} + τ _{t} and δ _{abct} is a fluctuation arising from natural variability and from the measurement process. Additionally, μ is an overall mean, α_{a} is the a-th row effect, β_{b} is the effect b-th column effect, ξ_{c} is the c-th layer effect, τ _{t} is the t-th time effect. Valuedata.frame with the following fields:
ReferencesBerke, O. (2001). Modified median polish kriging and its application to the wolfcamp - aquifer data. Environmetrics, 12(8):731-748.[link] Cressie, N. (1993). Statistics for spatial data. Wiley series in probability and statistics.[link] Examples
## Not run:
data(Metadb)
x<-matrix(0,1,37)
for(i in 1:37){
x[,i] <- 2007 + (seq(0, 36)/12)[i]
}
x<-as.Date (as.yearmon(x), frac = 1)
time = as.POSIXct(x, tz = "GMT")
MPST<-ConstructMPst(Metadb[,-c(1:4)],time,pts=Metadb[,2:4],Delta=c(7,6,5))
residuals<-removetrendMPst(MPST,eps=0.01, maxiter=2)
## End(Not run)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(STMedianPolish)
Loading required package: maptools
Loading required package: sp
Checking rgeos availability: TRUE
Loading required package: reshape2
Loading required package: spacetime
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/STMedianPolish/removetrendMPst.Rd_%03d_medium.png", width=480, height=480)
> ### Name: removetrendMPst
> ### Title: Median polish trend
> ### Aliases: removetrendMPst
>
> ### ** Examples
>
> ## Not run:
> data(Metadb)
> x<-matrix(0,1,37)
> for(i in 1:37){
+ x[,i] <- 2007 + (seq(0, 36)/12)[i]
+ }
> x<-as.Date (as.yearmon(x), frac = 1)
> time = as.POSIXct(x, tz = "GMT")
>
> MPST<-ConstructMPst(Metadb[,-c(1:4)],time,pts=Metadb[,2:4],Delta=c(7,6,5))
| | | 0% | |== | 3% | |==== | 5% | |====== | 8% | |======== | 11% | |========= | 14% | |=========== | 16% | |============= | 19% | |=============== | 22% | |================= | 24% | |=================== | 27% | |===================== | 30% | |======================= | 32% | |========================= | 35% | |========================== | 38% | |============================ | 41% | |============================== | 43% | |================================ | 46% | |================================== | 49% | |==================================== | 51% | |====================================== | 54% | |======================================== | 57% | |========================================== | 59% | |============================================ | 62% | |============================================= | 65% | |=============================================== | 68% | |================================================= | 70% | |=================================================== | 73% | |===================================================== | 76% | |======================================================= | 78% | |========================================================= | 81% | |=========================================================== | 84% | |============================================================= | 86% | |============================================================== | 89% | |================================================================ | 92% | |================================================================== | 95% | |==================================================================== | 97% | |======================================================================| 100%
> residuals<-removetrendMPst(MPST,eps=0.01, maxiter=2)
| | | 0% | |============ | 17% | |======================= | 33% | |=================================== | 50% | |=============================================== | 67% | |========================================================== | 83% | |======================================================================| 100%
> ## End(Not run)
>
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> dev.off()
null device
1
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