Description Usage Arguments Author(s) Examples
Call spaloess
function on the spatial domain in each month in parallel.
Every spatial domain uses the same smoothing parameters. NA observations will be
imputed.
1 2 | spaofit(input, output, info, model_control = spacetime.control(),
cluster_control = mapreduce.control())
|
input |
The path of input sequence file on HDFS. It should be by-month division. |
output |
The path of output sequence file on HDFS. It is also by-month division but with seasonal and trend components |
info |
The RData on HDFS which contains all station metadata. Make sure copy the RData of station_info to HDFS first using rhput. |
model_control |
Should be a list object generated from |
cluster_control |
Should be a list object generated from |
Xiaosu Tong
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## Not run:
FileInput <- "/tmp/bymth"
FileOutput <- "/tmp/bymthfit"
ccontrol <- mapreduce.control(libLoc=NULL, reduceTask=0)
mcontrol <- spacetime.control(
vari="resp", time="date", n=576, n.p=12, stat_n=7738,
s.window=13, t.window = 241, degree=2, span=0.015, Edeg=2
)
spaofit(
FileInput, FileOutput,
info="/tmp/station_info.RData",
model_control=mcontrol, cluster_control=ccontrol
)
## End(Not run)
|
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