Dear R users,
I am comparing two data sets (CO2 observation vs. CO2 simulation, during
1993-2002).
In order to do it I am calculating Root-Mean-Square(RMS) difference
with following formula:

> sqrt(sum((observed_residual - simulated_residual)^2)/n) # 'n' is number of
observations

Residuals are computed by fitting a harmonic function on both the data:
>testfit<-lm(co2obs~1+time+I(time^2)+sin(2*pi*time)+cos(2*pi*time)+sin(4*pi*time)+cos(4*pi*time)+sin(6*pi*time)+cos(6*pi*time)+sin(8*pi*time)+cos(8*pi*time),data=file)
#

>testfit1<-lm(co2model~1+time+I(time^2)+sin(2*pi*time)+cos(2*pi*time)+sin(4*pi*time)+cos(4*pi*time)+sin(6*pi*time)+cos(6*pi*time)+sin(8*pi*time)+cos(8*pi*time),data=file)#
'time' is time of observation

testfit$residuals # observed.residuals # (saved in seperate file by
write.table)
testfit1$residuals # modeled.residuals# (saved in seperate file by
write.table)


I am interested to to see climatology of RMS difference (all Jan months, all
Feb months, all March months,.............,all Dec months),
So I am computing like following:

time_span <- file[(file$mo==1),] # for 'Jan' month (similarly for other
months)
time_span
sub_seaobs <- (time_span$observed. residual)
sub_seaobs
sub_seatm3 <- (time_span$modeled.residual)
sub_seatm3
sqrt(sum((sub_seaobs-sub_seatm3)^2)/n) # 'n' is number of observation in
particular month

QUESTION:
I want to know if I am doing right and is it best way of computing
clomatology of Root-Mean-Square difference between two data sets.


-- 
Yogesh K. Tiwari (Dr.rer.nat),
Scientist,
Indian Institute of Tropical Meteorology,
Homi Bhabha Road,
Pashan,
Pune-411008
INDIA

Phone: 0091-99 2273 9513 (Cell)
        : 0091-20-258 93 600 (O) (Ext.250)
Fax    : 0091-20-258 93 825

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