This function uses original data to estimate new predicted values in each location and day.
gapFilling(prec, sts, inidate, enddate, parallel = TRUE, ncpu = 2, thres = NA)
A new file called Filled.RData
will be created in working directory. The load of this file (load('Filled.RData')
) will add a matrix containing the original data with missing values filled with this function. A new days
directory will be created in working path with one file per day. Each file contains a data.frame
with many rows as stations. The columns show the identifier (ID
)of each station; the observed value obs
(if exists); the binomial prediction predb
(dry<0.5; wet>=0.5); the raw prediction of precipitation magnitude pred1
resulting from models; the corrected magnitude prediction pred2
by binomial prediction (if dry, pred2==0); the final standardized magnitude prediction pred3
and the standard error err
of the model. All variables except predb
are in the same units as original values (mm*10).
Object of class matrix
containing the daily precipitation data. This dataset can be the cleaned.RData
resulting from qcPrec
function. Each column represents one station. The names of columns have to be names of the stations.
Object of class matrix
containing the stations info. Must have at least four fields: ID
: station identifier; ALT
: altitude; X
: Longitude in UTM projection (meters); and Y
: Latitude in UTM projection (meters). Tabulation separated.
Object of class Date
in format 'YYYY-mm-dd'
defining the first day of quality control process
Object of class Date
in format 'YYYY-mm-dd'
defining the last day of quality control process
Logical. If TRUE
, parallel computing is activated and the processes will be distributed among the ncpu
number of processor cores.
Only if parallel = TRUE
. Sets the number of processor cores used to parallel computing.
Threshold applied to search nearest stations. If thres=NA
the function will search 10 nearest observations without a distance limit. A positive number indicates the threshold in kilometers.
Roberto Serrano-Notivoli
#loads example data
data(precipDataset)
#runs function
gapFilling(prec=cleaned,sts=sts,inidate=as.Date('2001-01-01'),
enddate=as.Date('2001-01-02'),parallel=TRUE,ncpu=2,thres=NA)
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