ex_output_model_sensitivity

This dataset provides example output from the <code>model_sensitivity</code>
function, with sensitivity scores and associated uncertainties for each
indicator-pressure combination. Scores are based on time series data from
<code>pressure_ts_baltic</code> and <code>indicator_ts_baltic</code>.

datasets

Implementation of a modular framework for ecosystem risk assessments,
combining existing risk assessment approaches tailored to semi-quantitative and
quantitative analyses.

Helene Gutte

ecorisk

Risk Assessments for Ecosystems or Ecosystem Components

Saskia A. Otto

ex_output_model_sensitivity function

A data frame with 16 observations and 12 variables.<dl>
<dt>indicator</dt>
<dd>Names of the assessed indicator.</dd><dt>pressure</dt>
<dd>Names of the assessed pressure.</dd><dt>type</dt>
<dd>Type of effect (always direct + indirect for modelling pathway).</dd><dt>pathway</dt>
<dd>Pathway used to assess sensitivity.</dd><dt>sensitivity</dt>
<dd>Overall sensitivity score (-5 to 5).</dd><dt>adaptive_capacity</dt>
<dd>Adaptive capacity score (default is 0).</dd><dt>uncertainty_sens</dt>
<dd>Uncertainty score associated with sensitivity assessment (1 to 3).</dd><dt>uncertainty_ac</dt>
<dd>Uncertainty score associated with adaptive capacity (1 to 3).</dd><dt>r_sq</dt>
<dd>R-squared values from the GAM model, used for scoring.</dd><dt>p_value</dt>
<dd>P-values from the GAM model, determining statistical significance.</dd><dt>edf</dt>
<dd>Effective degrees of freedom from the GAM model, used to adjust scores based on non-linearity risk.</dd><dt>uncertainty_gam</dt>
<dd>Uncertainty score for sensitivity based on
predicted values from a GAM.</dd><dt>uncertainty_arima</dt>
<dd>Uncertainty score for sensitivity based on
predicted values from an ARIMA using the pressure variable as external
predictor.</dd>
</dl>

Format

Example output from the model_sensitivity() function based on time series — ex_output_model_sensitivity

A data frame with 16 observations and 12 variables.<dl>
<dt>indicator</dt>
<dd>Names of the assessed indicator.</dd>

<dt>pressure</dt>
<dd>Names of the assessed pressure.</dd>

<dt>type</dt>
<dd>Type of effect (always direct + indirect for modelling pathway).</dd>

<dt>pathway</dt>
<dd>Pathway used to assess sensitivity.</dd>

<dt>sensitivity</dt>
<dd>Overall sensitivity score (-5 to 5).</dd>

<dt>adaptive_capacity</dt>
<dd>Adaptive capacity score (default is 0).</dd>

<dt>uncertainty_sens</dt>
<dd>Uncertainty score associated with sensitivity assessment (1 to 3).</dd>

<dt>uncertainty_ac</dt>
<dd>Uncertainty score associated with adaptive capacity (1 to 3).</dd>

<dt>r_sq</dt>
<dd>R-squared values from the GAM model, used for scoring.</dd>

<dt>p_value</dt>
<dd>P-values from the GAM model, determining statistical significance.</dd>

<dt>edf</dt>
<dd>Effective degrees of freedom from the GAM model, used to adjust scores based on non-linearity risk.</dd>

<dt>uncertainty_gam</dt>
<dd>Uncertainty score for sensitivity based on
predicted values from a GAM.</dd>

<dt>uncertainty_arima</dt>
<dd>Uncertainty score for sensitivity based on
predicted values from an ARIMA using the pressure variable as external
predictor.</dd>


</dl>

ex_output_model_sensitivity: Example output from the `model_sensitivity()` function based on time series

Description

Usage

Arguments

Format