Standard GOF metrics Startvalues for sampling with nrChains > 1 : if you want to provide different start values for the different chains, provide a list

Standard GOF metrics Startvalues for sampling with nrChains > 1 : if you want to provide different start values for the different chains, provide a list

GOF(observed, predicted, plot = F)

Arguments

observed

observed values
predicted

predicted values
plot

should a plot be created

Value

A list with the following entries: rmse = root mean squared error, mae = mean absolute error, slope = slope of regression, offset = intercept of regression, R2 = R2 of regression

Details

The function considers predicted ~ observed and calculates

1) rmse = root mean squared error 2) mae = mean absolute errorr 3) a linear regression with slope, intercept and coefficient of determination R2

For the linear regression, the x axis is centered, meaning that the intercept is the difference between observed / predicted for the MEAN predicted value. This setting avoids a correlation between slope and intercept (that the intercept is != 0 as soon as the slope is !=0)

Examples


x = runif(500,-1,1)
y = 0.2 + 0.9  *x + rnorm(500, sd = 0.5)

summary(lm(y ~ x))
#> 
#> Call:
#> lm(formula = y ~ x)
#> 
#> Residuals:
#>      Min       1Q   Median       3Q      Max 
#> -1.44986 -0.30138 -0.02512  0.33049  1.66535 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept)  0.20840    0.02258    9.23   <2e-16 ***
#> x            0.88446    0.03645   24.27   <2e-16 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Residual standard error: 0.5041 on 498 degrees of freedom
#> Multiple R-squared:  0.5418,	Adjusted R-squared:  0.5409 
#> F-statistic: 588.9 on 1 and 498 DF,  p-value: < 2.2e-16
#> 

GOF(x,y)
#> $rmse
#> [1] 0.5506948
#> 
#> $mae
#> [1] 0.4308861
#> 
#> $slope
#> [1] 0.8844614
#> 
#> $offset
#> [1] 0.17963
#> 
#> $R2
#> [1] 0.5418068
#> 

GOF(x,y, plot = TRUE)
#> $rmse
#> [1] 0.5506948
#> 
#> $mae
#> [1] 0.4308861
#> 
#> $slope
#> [1] 0.8844614
#> 
#> $offset
#> [1] 0.17963
#> 
#> $R2
#> [1] 0.5418068
#>