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All functions

add_confint()
Add a confidence interval to an existing object
add_constant()
Add a constant to estimated values
add_fitted()
Add fitted values from a model to a data frame
add_fitted(<gam>)
Add fitted values from a GAM to a data frame
add_partial_residuals()
Add partial residuals
add_residuals()
Add residuals from a model to a data frame
add_residuals(<gam>)
Add residuals from a GAM to a data frame
add_sizer()
Add indicators of significant change after SiZeR
appraise()
Model diagnostic plots
basis()
Basis expansions for smooths
basis_size()
Extract basis dimension of a smooth
bird_move
Simulated bird migration data
check_user_select_smooths()
Select smooths based on user's choices
coef(<scam>)
Extract coefficients from a fitted scam model.
compare_smooths()
Compare smooths across models
confint(<fderiv>)
Point-wise and simultaneous confidence intervals for derivatives of smooths
confint(<gam>) confint(<gamm>) confint(<list>)
Point-wise and simultaneous confidence intervals for smooths
data_combos()
All combinations of factor levels plus typical values of continuous variables
data_sim()
Simulate example data for fitting GAMs
data_slice()
Prepare a data slice through model covariates
derivative_samples()
Posterior expectations of derivatives from an estimated model
derivatives()
Derivatives of estimated smooths via finite differences
difference_smooths()
Differences of factor smooth interactions
draw()
Generic plotting via ggplot2
draw(<basis>)
Plot basis functions
draw(<compare_smooths>)
Plot comparisons of smooths
draw(<derivatives>) draw(<partial_derivatives>)
Plot derivatives of smooths
draw(<difference_smooth>)
Plot differences of smooths
draw(<evaluated_parametric_term>)
Plot estimated parametric effects
draw(<gam>)
Plot estimated smooths from a fitted GAM
draw(<gamlss>)
Plot smooths of a GAMLSS model estimated by GJRM::gamlss
draw(<mgcv_smooth>)
Plot basis functions
draw(<pairwise_concurvity>) draw(<overall_concurvity>)
Plot concurvity measures
draw(<parametric_effects>)
Plot estimated effects for model parametric terms
draw(<penalty_df>)
Display penalty matrices of smooths using ggplot
draw(<rootogram>)
Draw a rootogram
draw(<smooth_estimates>)
Plot the result of a call to smooth_estimates()
draw(<smooth_samples>)
Plot posterior smooths
edf() model_edf()
Effective degrees of freedom for smooths and GAMs
eval_smooth()
S3 methods to evaluate individual smooths
evaluate_parametric_term()
Evaluate parametric model terms
evaluate_smooth()
Evaluate a smooth
evenly() seq_min_max()
Create a sequence of evenly-spaced values
factor_combos()
All combinations of factor levels
family(<gam>) family(<gamm>) family(<bam>) family(<list>)
Extract family objects from models
family_name()
Name of family used to fit model
family_type()
Extracts the type of family in a consistent way
fitted_samples()
Draw fitted values from the posterior distribution
fitted_values()
Generate fitted values from a estimated GAM
fix_offset()
Fix the names of a data frame containing an offset variable.
fixef
Extract fixed effects estimates
fixef(<gam>) fixef(<gamm>) fixef(<lm>) fixef(<glm>) fixed_effects()
Extract fixed effects estimates from a fitted GAM
gaussian_draws()
Posterior samples using a simple Metropolis Hastings sampler
get_by_smooth()
Extract an factor-by smooth by name
get_smooth()
Extract an mgcv smooth by name
get_smooths_by_id()
Extract an mgcv smooth given its position in the model object
gss_vocab
Data from the General Social Survey (GSS) from the National Opinion Research Center of the University of Chicago
gw_f0() gw_f1() gw_f2() gw_f3()
Gu and Wabha test functions
has_theta()
Are additional parameters available for a GAM?
is_by_smooth() is_factor_by_smooth() is_continuous_by_smooth() by_variable() by_level()
Tests for by variable smooths
is_factor_term()
Is a model term a factor (categorical)?
is_mgcv_smooth() stop_if_not_mgcv_smooth() check_is_mgcv_smooth() is_mrf_smooth()
Check if objects are smooths or are a particular type of smooth
is_offset()
Is a model term an offset?
link() inv_link() extract_link()
Extract link and inverse link functions from models
load_mgcv()
Load mgcv quietly
lp_matrix()
Return the linear prediction matrix of a fitted GAM
mh_draws()
Posterior samples using a Gaussian approximation to the posterior distribution
model_concurvity() concrvity()
Concurvity of an estimated GAM
model_vars()
List the variables involved in a model fitted with a formula
n_smooths()
How many smooths in a fitted model
nb_theta()
Negative binomial parameter theta
null_deviance()
Extract the null deviance of a fitted model
observed_fitted_plot()
Plot of fitted against observed response values
overview()
Provides an overview of a model and the terms in that model
parametric_effects()
Estimated values for parametric model terms
parametric_terms()
Names of any parametric terms in a GAM
partial_derivatives()
Partial derivatives of estimated multivariate smooths via finite differences
partial_residuals()
Partial residuals
penalty()
Extract and tidy penalty matrices
post_draws() generate_draws()
Low-level Functions to generate draws from the posterior distribution of model coefficients
posterior_samples()
Draw samples from the posterior distribution of an estimated model
predicted_samples()
Draw new response values from the conditional distribution of the response
qq_plot()
Quantile-quantile plot of model residuals
ref_level() level()
Return the reference or specific level of a factor
ref_sims
Reference simulation data
rep_first_factor_value()
Repeat the first level of a factor n times
residuals_hist_plot()
Histogram of model residuals
residuals_linpred_plot()
Plot of residuals versus linear predictor values
response_derivatives()
Derivatives on the response scale from an estimated GAM
rootogram()
Rootograms to assess goodness of model fit
seq_min_max_eps()
Create a sequence of evenly-spaced values adjusted to accommodate a small adjustment
shift_values()
Shift numeric values in a data frame by an amount eps
simulate(<gam>) simulate(<gamm>) simulate(<scam>)
Simulate from the posterior distribution of a GAM
smallAges
Lead-210 age-depth measurements for Small Water
smooth_coef_indices()
Indices of the parametric terms for a particular smooth
smooth_coefs()
Coefficients for a particular smooth
smooth_data()
Generate regular data over the covariates of a smooth
smooth_dim()
Dimension of a smooth
smooth_estimates()
Evaluate smooths at covariate values
smooth_label()
Extract the label for a smooth used by 'mgcv'
smooth_samples()
Posterior draws for individual smooths
smooth_terms()
List the variables involved in smooths
smooth_type()
Determine the type of smooth and return it n a human readable form
smooths()
Names of smooths in a GAM
spline_values()
Evaluate a spline at provided covariate values
term_names()
Extract names of all variables needed to fit a GAM or a smooth
term_variables()
Names of variables involved in a specified model term
theta()
General extractor for additional parameters in mgcv models
tidy_basis()
A tidy basis representation of a smooth object
to_na()
Sets the elements of vector to NA
too_far()
Exclude values that lie too far from the support of data
too_far_to_na()
Set rows of data to NA if the lie too far from a reference set of values
transform_fun()
Transform estimated values and confidence intervals by applying a function
typical_values()
Typical values of model covariates
user_draws()
Handle user-supplied posterior draws
variance_comp()
Variance components of smooths from smoothness estimates
vars_from_label()
Returns names of variables from a smooth label
which_smooths()
Identify a smooth term by its label
worm_plot()
Worm plot of model residuals
zooplankton
Madison lakes zooplankton data