Produce a 1-row data.frame of model metrics.
Usage
# S3 method for class 'loadLm'
summarizeModel(load.model, ...)Value
Returns a 1-row data frame with the following columns:
site.id- the unique identifier of the site, as inmetadata()constituent- the unique identifier of the constituent, as inmetadata()eqn- the regression equation, possibly in the formconst ~ model(x)wherexis theNumberof a pre-defined equation in rloadest::ModelsRMSE- the square root of the mean squared error. Errors will be computed from either fluxes or concentrations, as determined by the value ofpred.formatthat was passed toloadReg2()when this model was createdr.squared- the r-squared value, generalized for censored data, describing the amount of observed variation explained by the modelp.value- the p-value for the overall model fitcor.resid- the serial correlation of the model residualsPPCC- the probability plot correlation coefficient measuring the normality of the residualsIntercept,lnQ,lnQ2,DECTIME,DECTIME2,sin.DECTIME,cos.DECTIME, etc. - the fitted value of the intercept and other terms included in this model (list differs by model equation)Intercept.SE,lnQ.SE,lnQ2.SE,DECTIME.SE,DECTIME2.SE,sin.DECTIME.SE,cos.DECTIME.SE, etc. - the standard error of the fitted estimates of these termsIntercept.p.value,lnQ.p.value,lnQ2.p.value,DECTIME.p.value,DECTIME2.p.value,sin.DECTIME.p.value,cos.DECTIME.p.value- the p-values for each of these model terms
A 1-row data.frame of model metrics
See also
Other summarizeModel:
summarizeModel(),
summarizeModel.loadComp(),
summarizeModel.loadInterp(),
summarizeModel.loadModel(),
summarizeModel.loadReg2()
Examples
data(eg_loadLm)
summarizeModel(eg_loadLm)
#> site.id constituent eqn RMSE r.squared p.value
#> 1 01073500 NO3 log(NO3) ~ log(DISCHARGE) 0.3398085 0.05099499 0.1148298
#> cor.resid PPCC Intercept log(DISCHARGE) Intercept.SE log(DISCHARGE).SE
#> 1 0.2373998 0.9732018 -1.515114 -0.07824805 0.2562421 0.04872181
#> Intercept.p.value log(DISCHARGE).p.value
#> 1 3.405876e-07 0.1148298