transFun {spsh}

Parameter Transformation and Back-transformation

Description

Enables the transformation and backtransformation of parameters. This is widely considered advantageous during parameter estimation as the parameter space in the transformed is well-behaved, e.g. with normally distributed posteriors.

Usage

transFun(par.vec, trans.L)

Arguments

par.vec

Vector of n model parameters.

trans.L

list of n transformation/backtransformation operators, transformation and backtransformatio rules have to be antonyms and position in vector has to coincide with that in par.vec.

Details

Transformation rules are:

log10 \alpha_i,log10 n_i-1,log10 Ks,log10 \omega,log10 Ksc, and log10 Ksnc

.

Value

Returns transformed parameters as specificef by trans.L.

Note

The function is used to transform the parameter space and enabling optimisation or MCMC sampling to be more efficient.

Author(s)

Tobias KD Weber , [e-mail]

Examples

# van Genuchten-Mualem Model parameters
parL <- list("p" = c("thr"= 0.05, "ths" = 0.45, "alf1" = 0.01, "n" = 2, "Ks" = 100, "tau" = .5),
             "psel" = c(1, 1, 0, 1, 1, 1),
             "plo" = c(0.001 , 0.2, 0.001, 1.1, 1, -2),
             "pup" = c(0.3, 0.95, 1, 10, 1e4, 10)
)
# Two lists, one with function to transform, the other to back-transform model parameters
ptransfit <- c(function(x)x, function(x)x,log10,function(x)log10(x-1),log10, function(x)x)
pretransfit <- c(function(x)x, function(x)x,function(x)10^x, 
                 function(x)10^x+1,function(x)10^x,function(x)x)
# Transform
p_trans <- transFun(parL$p, ptransfit)