get.Li: Downward Longwave Radiation from a emissivity and a cloud...
In roilanhv/ROLi: Evaluate various downward longwave parametrizations

Downward Longwave Radiation from a emissivity and a cloud cover schemes

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get.Li(data_, E_fun = "EAN", C_fun = "-", adjust = FALSE,
  method = c("non-linear", "montecarlo"), nsample = 1000, max_iter = 10,
  stats = "rmse", log_file = NULL, ret_coefs = FALSE, forced = TRUE)

`data_`	Data frame with column of date (date), temperature (Ta), partial vapor pressure (es), potencial radiation (Rpot), relative humidity (rh), atennuation index (K)
`E_fun`	Emissivity scheme
`C_fun`	Cloud cover scheme
`adjust`	FALSE, TRUE if nonlinear least square adjusting wanted
`method`	"non-linear" (default) for Non linear Least Square adjust, "montecarlo" for MonteCarlo optimization. Later be usseful when a NLS can't adjust observed data allowing optimization.
`nsample`	population number evaluated in each iteration (only when method = "montecarlo").
`max_iter`	maximun number of iterations (only when method = "montecarlo").
`stats`	statistical function to be minimized (only when method = "montecarlo"), NOTE: the best result should be 0.0 (ex., if stats = r (correlation), then transform to rMod = 1.0 - r, so the best result is when r== 1.0, so rMod == 0.0)
`log_file`	path to a log file
`ret_coefs`	Return coeficients from adjusting, in this case a list contein both information: estimated Li and coeficients used or determined.
`forced`	Forced adjust, default TRUE