hydroGOF (version 0.4-0)

ssq: Sum of the Squared Residuals

Description

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.

Usage

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, ...)

Arguments

sim

numeric, zoo, matrix or data.frame with simulated values

obs

numeric, zoo, matrix or data.frame with observed values

na.rm

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.

Value

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.

Examples

# 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)
# }