EDMfun0

Estimates future states of xt based on based behaviour

Includes a collection of functions presented in "Measuring stability in ecological systems without static equilibria" by Clark et al. (2022) <doi:10.1002/ecs2.4328> in Ecosphere.
These can be used to estimate the parameters of a stochastic state space model (i.e. a model where
a time series is observed with error). The goal of this package is to estimate the variability
around a deterministic process, both in terms of observation error - i.e. variability due to
imperfect observations that does not influence system state - and in terms of process noise - i.e.
stochastic variation in the actual state of the process. Unlike classical methods for estimating
variability, this package does not necessarily assume that the deterministic state is fixed (i.e.
a fixed-point equilibrium), meaning that variability around a dynamic trajectory can be estimated
(e.g. stochastic fluctuations during predator-prey dynamics).

Adam Clark

pttstability

Particle-Takens Stability

EDMfun0 function

<dl><dt>smp_cf</dt>
<dd>a matrix of s-map coefficients. Columns correspond to intercept and time lags, rows to observations. Final column corresponds to intercept term.</dd>
<dt>yp</dt>
<dd>a matrix of covariates to be multiplied by the smp_cf (typically time lags). Should have one fewer column than smp_cf.</dd>
<dt>x</dt>
<dd>observation at time-1, to be used to make the prediction.</dd>
<dt>minest</dt>
<dd>minimum value to return for prediction - defaults to 0.</dd>
<dt>maxest</dt>
<dd>maximum value to return for prediction - defaults to NULL (no maximum)</dd>
<dt>time</dt>
<dd>the time step (i.e. position in smp_cf) for the desired prediction. Prediction will be made based on observation in preceding time point (i.e. time-1).</dd></dl>

Arguments

EDM deterministic function — EDMfun0

<dl>

<dt>smp_cf</dt>
<dd>a matrix of s-map coefficients. Columns correspond to intercept and time lags, rows to observations. Final column corresponds to intercept term.</dd>


<dt>yp</dt>
<dd>a matrix of covariates to be multiplied by the smp_cf (typically time lags). Should have one fewer column than smp_cf.</dd>


<dt>x</dt>
<dd>observation at time-1, to be used to make the prediction.</dd>


<dt>minest</dt>
<dd>minimum value to return for prediction - defaults to 0.</dd>


<dt>maxest</dt>
<dd>maximum value to return for prediction - defaults to NULL (no maximum)</dd>


<dt>time</dt>
<dd>the time step (i.e. position in smp_cf) for the desired prediction. Prediction will be made based on observation in preceding time point (i.e. time-1).</dd>

</dl>

EDMfun0: EDM deterministic function

Description

Usage

Value

Arguments