sum_stat: Caclulate summary stats of mod v obs

In tadhg-moore/gotmtools: Tools to work with GOTM input data and also process the output data

Description

Calculate general summary statistics of modelled water temperature vs observed water temperature; Pearson's R, variance, covariance, bias, Nash-Sutcliffe Efficiency (NSE) and Root mean squared error (RMSE).

Usage

sum_stat(mod, obs, depth = F, na.rm = T, depth.range = NULL)

Arguments

mod	vector or dataframe; Vector if no depth values otherwise Modelled values in the long format. i.e. same as observed in ACPy
obs	vector or dataframe; Vector if no depth values otherwise Observed values in the long format loaded in using load.obs
depth	logical; Depth values are included. Defaults to False
na.rm	logical; Remove NA'values
depth.range	vector; vector with a depth range to extract statistics at certain depths. Upper limit first e.g. c(-5,-10). Defaults to whole depth range.

Value

data frame of summary statistics

tadhg-moore/gotmtools documentation built on Oct. 9, 2019, 2:48 p.m.