cleandat {wsyn} | R Documentation |
Clean (spatio)temporal data matrices to make them ready for analyses using the wsyn
package
Description
A data cleaning function for optimal Box-Cox transformation, detrending, standarizing variance, de-meaning
Usage
cleandat(dat, times, clev, lambdas = seq(-10, 10, by = 0.01), mints = NA)
Arguments
dat |
A locations x time data matrix, or a time series vector (for 1 location) |
times |
The times of measurement, spacing 1 |
clev |
The level of cleaning to do, 1 through 5. See details. |
lambdas |
A vector of lambdas to test for optimal Box-Cox transformation, if Box-Cox is
performed. Ignored for |
mints |
If |
Details
NAs, Infs, etc. in dat
trigger an error. If clev==1
, time series are (individually)
de-meaned. If clev==2
, time series are (individually) linearly detrended and de-meaned. If clev==3
,
time series are (individually) linearly detrended and de-meaned, and variances are standardized to 1. If
clev==4
, an optimal Box-Cox normalization procedure is applied jointly to all time series (so the same
Box-Cox transformation is applied to all time series after they are individually shifted depending on the value
of mints
). Transformed time series are then individually linearly detrended, de-meaned, and variances are
standardized to 1. If clev==5
, an optimal Box-Cox normalization procedure is applied to each time series
individually (again after individually shifting according to mints
), and transformed time series are then
individually linearly detrended, de-meaned, and variances are standardized to 1. Constant time series and perfect
linear trends trigger an error for clev>=3
. If clev>=4
and the optimal lambda
for one or
more time series is a boundary case or if there is more than one optimal lambda, it triggers a warning. A wider
range of lambda
should be considered in the former case.
Value
cleandat
returns a list containing the cleaned data, clev
, and the optimal
lambdas from the Box-Cox procedure (NA
for clev<4
, see details).
Author(s)
Jonathan Walter, jaw3es@virginia.edu; Lawrence Sheppard, lwsheppard@ku.edu; Daniel Reuman, reuman@ku.edu; Lei Zhao, lei.zhao@cau.edu.cn
References
Box, GEP and Cox, DR (1964) An analysis of transformations (with discussion). Journal of the Royal Statistical Society B, 26, 211–252.
Venables, WN and Ripley, BD (2002) Modern Applied Statistics with S. Fourth edition. Springer.
Sheppard, LW, et al. (2016) Changes in large-scale climate alter spatial synchrony of aphid pests. Nature Climate Change. DOI: 10.1038/nclimate2881
See Also
wt
, wmf
, wpmf
, coh
, wlm
,
wlmtest
, clust
, browseVignettes("wsyn")
Examples
times<-1:100
dat<-rnorm(100)
res1<-cleandat(dat,times,1) #this removes the mean
res2<-cleandat(dat,times,2) #detrends and removes the mean
res3<-cleandat(dat,times,3) #variances also standardized
res4<-cleandat(dat,times,4) #also joint Box-Cox applied
res5<-cleandat(dat,times,5) #1-3, also indiv Box-Cox