Computing residual sum of squares for predictions vs. data of NEE

Computing residual sum of squares for predictions vs. data of NEE

LRC_computeCost(
  thetaOpt,
  theta,
  iOpt,
  flux,
  sdFlux,
  parameterPrior,
  sdParameterPrior,
  ...
)

Arguments

thetaOpt

numeric vector of optimized parameters

theta

numeric vector of parameters

iOpt

integer vector of positions of parameters that are optimized

flux

numeric: NEP (-NEE) or GPP time series umolCO2 / m2 / s, should not contain NA

sdFlux

numeric: standard deviation of Flux umolCO2 / m2 / s, should not contain NA

parameterPrior

numeric vector along theta: prior estimate of parameter (range of values)

sdParameterPrior

standard deviation of parameterPrior

...

other arguments to LRC_predictLRC(), such as VPD0, fixVPD

weightMisfitPar2000

weight of misfit of difference between saturation and prediction at PAR = 2000

Value

numeric: residual sum of squares