sim_nlf function

Define a non-linear relationship

Closure to be used in sim_distribution.

sim_nlf(
  formula = ~alpha - ((depth - mu)^2)/(2 * sigma^2),
  coeff = list(alpha = 0, mu = 200, sigma = 70)
)

Arguments

• formula: Formula describing parametric relationships between data and coefficients. The data used in sim_distribution are grid coordinates expanded across ages and years (i.e., includes columns "x", "y", "depth", "cell", "division", "strat", "age", "year"). Values of the coefficients must be included in argument coeff as a named list.
• coeff: Named list of coefficient values used in formula.

Returns

Returns a function for use inside sim_distribution.

Examples

## Make a grid and replicate data for 5 ages and 5 years
## (This is similar to what happens inside sim_distribution)
grid <- make_grid(shelf_width = 10)
grid_xy <- data.frame(grid)
i <- rep(seq(nrow(grid_xy)), times = 5)
a <- rep(1:5, each = nrow(grid_xy))
grid_xy <- grid_xy[i, ]
grid_xy$age <- a
i <- rep(seq(nrow(grid_xy)), times = 5)
y <- rep(1:5, each = nrow(grid_xy))
grid_xy <- grid_xy[i, ]
grid_xy$year <- y

## Now using sim_nlf, produce a function to apply to the expanded grid_xy data
## For this firs example, the depth effect is parabolic and the vertex is deeper by age
## (i.e., to impose ontogenetic deepening)
nlf <- sim_nlf(formula = ~ alpha - ((depth - mu + beta * age) ^ 2) / (2 * sigma ^ 2),
               coeff = list(alpha = 0, mu = 200, sigma = 70, beta = -70))
grid_xy$depth_effect <- nlf(grid_xy)

library(plotly)
grid_xy %>%
  filter(year == 1) %>%
  plot_ly(x = ~depth, y = ~depth_effect, split = ~age) %>%
  add_lines()