logLikFun.norm: Calculation of the Log-likelihood assuming Identially,...
In spsh: Estimation and Prediction of Parameters of Various Soil Hydraulic Property Models

Description Usage Arguments Details Value Note Author(s) References Examples

Calculates the i-th log-likelihood of each y-yhat pair as described in \insertCiteSeber.2004spsh.

1	logLikFun.norm(y, yhat, sigma)

`y`	A vector of `n` observed properties/variables of interest.
`yhat`	A vector of `n` model simulated properties/variables of interest.
`sigma`	A vector of length 1 considering homoscedastic residuals.

The underlying assumption is, that the model residuals (errors) are independently, and identically distributed (i.i.d.) following a normal distribution. Alternatively consider using dnorm.

log-likelihood value of an normal distribution with N~(0, sigma^2)

The assumption of i.i.d. and normal distribution is best investigated a posteriori.

Tobias KD Weber , tobias.weber@uni-hohenheim.de

\insertRef

Seber.2004spsh

# homoscedastic residuals
sig.s  <- .01
y.scat <- rnorm(100, 0, sig.s)
yhat   <- (1:100)^1.2
y      <- yhat + y.scat
sum(logLikFun.norm(y, yhat, sig.s))
plot(yhat-y)