calculate_errors(): the
mat_U_error element in the returned list was incorrectly
named ,mat_U_error when type = "sem", causing
NULL to be returned on access.driven_vital_rate():
conditions length(slope > 1) and
length(error_sd > 1) were always evaluating to
TRUE regardless of input, preventing correct handling of
matrix inputs.rand_leslie_set()
for the Siler mortality model (b_0 and b_1
were drawn from the same ranges as a_0 and
a_1) and for multi-parameter fecundity models
(logistic, vonBertalanffy,
normal, hadwiger), where all parameters were
incorrectly drawn from the first row of
fecundity_params.add_mpm_error_indiv() that had no effect.generate_mpm_set() and
random_mpm()model_reproduction() is
synonymous with model_fertility and
model_fecundity.CompadreDB
objects, the archetype (Lefkovitch) or model parameters (Leslie), are
now included as metadata.rand_leslie_set() to generate sets of
Leslie matrices where the parameters of the constituent mortality and
fertility functions are drawn randomly from defined distributions. The
function returns a CompadreDB object by default, but can
also be set to produce lists of MPMs or life tables.generate_mpm_set() is now deprecated, and will be
removed at a later date. Users should use rand_lefko_set()
instead.random_mpm() is now deprecated, and will be removed at
a later date. Users should use rand_lefko_mpm()
instead.split, by_type and as_compadre,
which governed output types in generate_mpm_set(). These
arguments been replaced with a simpler and more transparent argument,
output.compute_ci_U() which calculates
confidence intervals for traits derived from matrix models where only
the U submatrix is used. For example, life expectancy (using the
function Rage::life_expect_mean()).MCMCpack, which is reportedly
being archived from CRAN. This change means that previous versions of
mpmsim may not function correctly and it is advisable to
update to the new version.random_mpm().
Now the values are provided as mean fecundity and can be provided as a
range of values, whereby a value is drawn from a random uniform
distribution. This is the best way to create a set of models with
different fecundity properties.drive_vital_rate().model_mortality() as an alias for
model_survival().generate_mpm_set() now returns a
CompadreDB object by default.testthat. Test
coverage 97.17%.generate_mpm_set() andrandom_mpm().make_leslie_mpm(), which can make use of outputs from
functions for describing demographic trajectories
(model_fertility() and model_survival()).add_mpm_error(), calculate_errors() and
compute_ci().plot_matrix()
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