Function reference

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>)
 Pointwise and simultaneous confidence intervals for derivatives of smooths

confint(<gam>)
confint(<gamm>)
confint(<list>)
 Pointwise 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 evenlyspaced 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 factorby 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

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()
 Lowlevel 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()
 Quantilequantile 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 evenlyspaced 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
 Lead210 agedepth 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 usersupplied 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