View source: R/pred_kernel_funcs.R
power_law_pred_kernel | R Documentation |
This predation kernel is a power-law, with sigmoidal cut-offs at large and small predator/prey mass ratios.
power_law_pred_kernel(
ppmr,
kernel_exp,
kernel_l_l,
kernel_u_l,
kernel_l_r,
kernel_u_r
)
ppmr |
A vector of predator/prey size ratios at which to evaluate the predation kernel. |
kernel_exp |
The exponent of the power law |
kernel_l_l |
The location of the left, rising sigmoid |
kernel_u_l |
The shape of the left, rising sigmoid |
kernel_l_r |
The location of the right, falling sigmoid |
kernel_u_r |
The shape of the right, falling sigmoid |
The return value is calculated as
ppmr^kernel_exp /
(1 + (exp(kernel_l_l) / ppmr)^kernel_u_l) /
(1 + (ppmr / exp(kernel_l_r))^kernel_u_r)
The parameters need to be given as columns in the species parameter dataframe.
A vector giving the value of the predation kernel at each of the
predator/prey mass ratios in the ppmr
argument.
setPredKernel()
Other predation kernel:
box_pred_kernel()
,
lognormal_pred_kernel()
,
truncated_lognormal_pred_kernel()
params <- NS_params
# Set all required paramters before changing kernel type
species_params(params)["Cod", "kernel_exp"] <- -0.8
species_params(params)["Cod", "kernel_l_l"] <- 4.6
species_params(params)["Cod", "kernel_u_l"] <- 3
species_params(params)["Cod", "kernel_l_r"] <- 12.5
species_params(params)["Cod", "kernel_u_r"] <- 4.3
species_params(params)["Cod", "kernel_type"] <- "power_law"
plot(w_full(params), getPredKernel(params)["Cod", 10, ], type="l", log="x")
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