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

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

RectangularLRCFitterCVersion_computeCost(
  thetaOpt,
  theta,
  iOpt,
  flux,
  sdFlux,
  parameterPrior,
  sdParameterPrior,
  ...,
  VPD0 = 10,
  fixVPD = (k == 0)
)

Arguments

thetaOpt

parameter vector with components of theta0 that are optimized

theta

parameter vector with positions as in argument of LRC_getParamNames()

iOpt

position in theta 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

VPD0

VPD0 hPa -> Parameters VPD0 fixed to 10 hPa according to Lasslop et al 2010

fixVPD

boolean scalar or vector of nrow theta:fixVPD if TRUE the VPD effect is not considered and VPD is not part of the computation