Sum of the Squared Residuals between sim
and obs
, with treatment of missing values. Its units are the squared measurement units of sim
and obs
.
ssq(sim, obs, ...)# S3 method for default
ssq(sim, obs, na.rm = TRUE, ...)
# S3 method for data.frame
ssq(sim, obs, na.rm=TRUE, ...)
# S3 method for matrix
ssq(sim, obs, na.rm=TRUE, ...)
numeric, zoo, matrix or data.frame with simulated values
numeric, zoo, matrix or data.frame with observed values
a logical value indicating whether 'NA' should be stripped before the computation proceeds.
When an 'NA' value is found at the i-th position in obs
OR sim
, the i-th value of obs
AND sim
are removed before the computation.
further arguments passed to or from other methods.
Sum of the squared residuals between sim
and obs
.
If sim
and obs
are matrixes, the returned value is a vector, with the SSR between each column of sim
and obs
.
# NOT RUN {
obs <- 1:10
sim <- 1:10
ssq(sim, obs)
obs <- 1:10
sim <- 2:11
ssq(sim, obs)
##################
# Loading daily streamflows of the Ega River (Spain), from 1961 to 1970
data(EgaEnEstellaQts)
obs <- EgaEnEstellaQts
# Generating a simulated daily time series, initially equal to the observed series
sim <- obs
# Computing the 'rNSeff' for the "best" (unattainable) case
ssq(sim=sim, obs=obs)
# Randomly changing the first 2000 elements of 'sim', by using a normal distribution
# with mean 10 and standard deviation equal to 1 (default of 'rnorm').
sim[1:2000] <- obs[1:2000] + rnorm(2000, mean=10)
# Computing the new 'rNSeff'
ssq(sim=sim, obs=obs)
# }
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