likelihood_EDM_piecewise

Calculates likelihoods across several segments of data - e.g. multiple plots from a single experiment.
See documentation for particleFilterLL_piecewise for examples of use.

regression

filter

particle

dewdrop

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

likelihood_EDM_piecewise function

<dl><dt>param</dt>
<dd>parameters to be passed to likelihood0 function</dd>
<dt>y</dt>
<dd>the time series to be analyzed</dd>
<dt>libuse_y</dt>
<dd>a matrix with two columns, specifying the start end end positions of segments within vector y</dd>
<dt>smap_coefs</dt>
<dd>a matrix of s-mapping coefficients</dd>
<dt>Euse</dt>
<dd>embedding dimension for the s-mapping analysis</dd>
<dt>tuse</dt>
<dd>theta for s-mapping analysis</dd>
<dt>N</dt>
<dd>number of particles</dd>
<dt>colpar</dt>
<dd>parameters to be passed to the colfun0 - defaults to c(logit(1e-6), log(0.1))</dd></dl>

Arguments

calculate likelihood for piecewise data — likelihood_EDM_piecewise

<dl>

<dt>param</dt>
<dd>parameters to be passed to likelihood0 function</dd>


<dt>y</dt>
<dd>the time series to be analyzed</dd>


<dt>libuse_y</dt>
<dd>a matrix with two columns, specifying the start end end positions of segments within vector y</dd>


<dt>smap_coefs</dt>
<dd>a matrix of s-mapping coefficients</dd>


<dt>Euse</dt>
<dd>embedding dimension for the s-mapping analysis</dd>


<dt>tuse</dt>
<dd>theta for s-mapping analysis</dd>


<dt>N</dt>
<dd>number of particles</dd>


<dt>colpar</dt>
<dd>parameters to be passed to the colfun0 - defaults to c(logit(1e-6), log(0.1))</dd>

</dl>

likelihood_EDM_piecewise: calculate likelihood for piecewise data

Description

Usage

Value

Arguments