EGRET (version 2.3.0)

modelEstimation: Estimation process for the WRTDS (Weighted Regressions on Time, Discharge, and Season)

Description

This one function does a jack-knife cross-validation of a WRTDS model, fits the surface (concentration as a function of discharge and time), estimates daily values of concentration and flux, and flow normalized values. It returns a named list with the following dataframes: Daily, INFO, Sample, and the matrix: surfaces.

Usage

modelEstimation(eList, windowY = 7, windowQ = 2, windowS = 0.5,
  minNumObs = 100, minNumUncen = 50, edgeAdjust = TRUE)

Arguments

eList

named list with at least the Daily, Sample, and INFO dataframes

windowY

numeric specifying the half-window width in the time dimension, in units of years, default is 7

windowQ

numeric specifying the half-window width in the discharge dimension, units are natural log units, default is 2

windowS

numeric specifying the half-window with in the seasonal dimension, in units of years, default is 0.5

minNumObs

numeric specifying the miniumum number of observations required to run the weighted regression, default is 100

minNumUncen

numeric specifying the minimum number of uncensored observations to run the weighted regression, default is 50

edgeAdjust

logical specifying whether to use the modified method for calculating the windows at the edge of the record. The modified method tends to reduce curvature near the start and end of record. Default is TRUE.

Value

• eList named list with Daily, Sample, and INFO dataframes, along with the surfaces matrix. Any of these values can be NA, not all EGRET functions will work with missing parts of the named list eList.

Examples

eList <- Choptank_eList
#Run an estimation adjusting windowQ from default:
eList <- modelEstimation(eList, windowQ=5)