all_results_ex: Output tibble after applying all IND~pressure modeling...
In saskiaotto/INDperform: Evaluation of Indicator Performances for Assessing Ecosystem States
Description
This is an example output tibble based on the Central Baltic Sea
food web indicator demonstration data after applying the calc_deriv
and the test_interaction functions on the
merge_models_ex tibble.
Usage
1
Format
A data frame with 84 rows and 31 variables:
idNumerical IDs for the IND~press combinations.
indIndicator names.
pressPressure names.
model_typeSpecification of the model type; at this stage containing only
"gam" (Generalized Additive Model).
corrstrucSpecification of the correlation structure; at this stage
containing only "none".
aicAIC of the fitted models
edfEstimated degrees of freedom for the model terms.
p_valThe p values for the smoothing term (the pressure).
signif_codeThe significance codes for the p-values.
r_sqThe adjusted r-squared for the models. Defined as the proportion
of variance explained, where original variance and residual variance are
both estimated using unbiased estimators. This quantity can be negative
if your model is worse than a one parameter constant model, and can be
higher for the smaller of two nested models.
expl_devThe proportion of the null deviance explained by the models.
nrmseAbsolute values of the root mean square error normalized by the
standard deviation (NRMSE) and corrected for the prior (log) transformation.
ks_testThe p-values from a Kolmogorov-Smirnov Test applied on the model
residuals to test for normal distribution. P-values > 0.05 indicate
normally distributed residuals.
taclogical; indicates whether temporal autocorrelation (TAC) was detected
in the residuals. TRUE if model residuals show TAC.
pres_outlierA list-column with outliers identified for each model (i.e.
Cook's distance > 1). The indices present the position in
the training data, including NAs.
excl_outlierA list-column listing all outliers per model that have been
excluded in the GAM fitting
modelA list-column of IND~press-specific gam objects.
propThe proportion of the observed pressure range where the
indicator shows a response (see the last section in Details)
zero_in_confA list-column of logical vectors indicating for
every pressure value (in press_seq) whether the slope of the indicator
response at that pressure value is within the confidence interval,
i.e. is zero.
zic_start_endA list-column of logical vectors indicating for
every pressure value (in press_seq) whether the slope is considered
as zero for the proportion calculation (see see the last section in
Details)
.
press_seqA list-column with sequences of 100 evenly spaced pressure
values.
predA list-column with the predicted indicator responses
averaged across all bootstraps (for the 100 equally spaced
pressure values).
pred_ci_upA list-column with the upper confidence limit of the
bootstrapped predictions.
pred_ci_lowA list-column with the lower confidence limit of the
bootstrapped predictions.
deriv1A list-column with the first derivatives of the indicator responses
averaged across all bootstraps (for the 100 equally spaced
pressure values).
deriv1_ci_upA list-column with the upper confidence limit of the
bootstrapped first derivatives.
deriv1_ci_lowA list-column with the lower confidence limit of the
bootstrapped first derivatives.
adj_n_bootThe number of successful bootstrap samples that was
actually used for calculating the mean and confidence intervals of
the predicted indicator response and the derivative.
boot_errorA list-column capturing potential error messages that
occurred as side effects when refitting the GAM(M)s on each bootstrap
sample.
interactionlogical; if TRUE, at least one thresh_gam
performs better than its corresponding gam based on the leave-one-out
cross-validation.
thresh_varA list-column with the threshold variables of the
better performing thresh_models.
thresh_modelsA list-column with nested lists containing the
better performing thresh_models.
thresh_errorA list-column capturing potential error messages that
occurred as side effects when fitting each threshold GAMs and performing the
LOOCV.
tac_in_threshlogical vector; indicates for every listed
thresh_model whether temporal autocorrelation (TAC) was
detected in the residuals. TRUE if model residuals show TAC.
saskiaotto/INDperform documentation built on Oct. 27, 2021, 10:33 p.m.
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Description
This is an example output tibble based on the Central Baltic Sea
food web indicator demonstration data after applying the calc_deriv
and the test_interaction functions on the
merge_models_ex tibble.
Usage
1 |
Format
A data frame with 84 rows and 31 variables:
idNumerical IDs for the IND~press combinations.
indIndicator names.
pressPressure names.
model_typeSpecification of the model type; at this stage containing only "gam" (Generalized Additive Model).
corrstrucSpecification of the correlation structure; at this stage containing only "none".
aicAIC of the fitted models
edfEstimated degrees of freedom for the model terms.
p_valThe p values for the smoothing term (the pressure).
signif_codeThe significance codes for the p-values.
r_sqThe adjusted r-squared for the models. Defined as the proportion of variance explained, where original variance and residual variance are both estimated using unbiased estimators. This quantity can be negative if your model is worse than a one parameter constant model, and can be higher for the smaller of two nested models.
expl_devThe proportion of the null deviance explained by the models.
nrmseAbsolute values of the root mean square error normalized by the standard deviation (NRMSE) and corrected for the prior (log) transformation.
ks_testThe p-values from a Kolmogorov-Smirnov Test applied on the model residuals to test for normal distribution. P-values > 0.05 indicate normally distributed residuals.
taclogical; indicates whether temporal autocorrelation (TAC) was detected in the residuals. TRUE if model residuals show TAC.
pres_outlierA list-column with outliers identified for each model (i.e. Cook's distance > 1). The indices present the position in the training data, including NAs.
excl_outlierA list-column listing all outliers per model that have been excluded in the GAM fitting
modelA list-column of IND~press-specific gam objects.
propThe proportion of the observed pressure range where the indicator shows a response (see the last section in Details)
zero_in_confA list-column of logical vectors indicating for every pressure value (in press_seq) whether the slope of the indicator response at that pressure value is within the confidence interval, i.e. is zero.
zic_start_endA list-column of logical vectors indicating for every pressure value (in press_seq) whether the slope is considered as zero for the proportion calculation (see see the last section in Details)
.
press_seqA list-column with sequences of 100 evenly spaced pressure values.
predA list-column with the predicted indicator responses averaged across all bootstraps (for the 100 equally spaced pressure values).
pred_ci_upA list-column with the upper confidence limit of the bootstrapped predictions.
pred_ci_lowA list-column with the lower confidence limit of the bootstrapped predictions.
deriv1A list-column with the first derivatives of the indicator responses averaged across all bootstraps (for the 100 equally spaced pressure values).
deriv1_ci_upA list-column with the upper confidence limit of the bootstrapped first derivatives.
deriv1_ci_lowA list-column with the lower confidence limit of the bootstrapped first derivatives.
adj_n_bootThe number of successful bootstrap samples that was actually used for calculating the mean and confidence intervals of the predicted indicator response and the derivative.
boot_errorA list-column capturing potential error messages that occurred as side effects when refitting the GAM(M)s on each bootstrap sample.
interactionlogical; if TRUE, at least one thresh_gam performs better than its corresponding gam based on the leave-one-out cross-validation.
thresh_varA list-column with the threshold variables of the better performing thresh_models.
thresh_modelsA list-column with nested lists containing the better performing thresh_models.
thresh_errorA list-column capturing potential error messages that occurred as side effects when fitting each threshold GAMs and performing the LOOCV.
tac_in_threshlogical vector; indicates for every listed thresh_model whether temporal autocorrelation (TAC) was detected in the residuals. TRUE if model residuals show TAC.
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