model_gam_ex: Model output tibble from the 'model_gam' function
In saskiaotto/INDperform: Evaluation of Indicator Performances for Assessing Ecosystem States
Description
This is an example output tibble from the model_gam function applied
on the Central Baltic Sea food web indicator demonstration data.
Usage
1
Format
A data frame with 84 rows and 17 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) using no back-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.
saskiaotto/INDperform documentation built on Oct. 27, 2021, 10:33 p.m.
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Description
This is an example output tibble from the model_gam function applied
on the Central Baltic Sea food web indicator demonstration data.
Usage
1 |
Format
A data frame with 84 rows and 17 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) using no back-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.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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