Description Usage Arguments Details
For quadratic models predicting responses across an environmental gradients, extract the response and metrics (optimum value, e.g.)
get_response
: Get model predicted response across a range of depth and temperature values
psi.opt
: Optimum environmental value
psi.tol
: Tolerance across environmental values
psi.max
: Response achieved at environmental optimum
1 2 3 4 5 6 7 |
alphas |
a data.table with alpha values; rows are posterior iterations, a1,a2,a3,a4,a5 are columns (see details) |
X |
a data.table with columns for |
n_samp |
integer indicating (random) subsample of posterior to use; if NULL (default), no subsampling is performed |
n_grid |
number of depth and temperature values over which to estimate response; if NULL (default), response is calculated only for observed combinations in |
b1 |
a linear coefficient value (like a2 or a4 in |
b2 |
a quadratic coefficient value (like a3 or a5 in |
b0 |
an intercept parameter value (like a1 in |
The columns in alphas
are parameters estimated from the MSOM model. The MSOM model has a form of y=a1*1 + a2*bt+a3*bt^2 + a4*depth+a5*depth^2
. Thus, the columns in alpha are interpreted as follows:
a1 | an intercept term, corresponds to b0 |
a2 | a linear coefficient associated with bottom temeprature, corresponds to b1 |
a3 | a quadratic coefficient associated with bottom temperature, corresponds to b2 |
a4 | a linear coefficient associated with depth, corresponds to b1 |
a5 | a quadratic coefficient assoicated with depth, corresponds to b2 |
where b0
, b1
, b2
are arguments to the response metric functions (psi.opt
, psi.tol
, and psi.max
). Note, then, that the response metric functions do not consider models with 2 predictors, but only 1, hence the different notation.
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