Package index • gratia

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_fitted_samples() add_predicted_samples() add_posterior_samples() add_smooth_samples(): Add posterior draws from a model to a data object

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

boundary() experimental: Extract the boundary of a soap film smooth

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

conditional_values(): Conditional predictions from a GAM

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

dispersion() experimental: Dispersion parameter for fitted model

draw(): Generic plotting via ggplot2

draw(<basis>): Plot basis functions

draw(<compare_smooths>): Plot comparisons of smooths

draw(<conditional_values>): Plot conditional predictions

draw(<derivatives>) draw(<partial_derivatives>): Plot derivatives of smooths

draw(<difference_smooth>): Plot differences of smooths

draw(<evaluated_parametric_term>) deprecated: 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() deprecated: Evaluate parametric model terms

evaluate_smooth() deprecated: 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_constant() experimental: Extract the model constant term

model_vars(): List the variables involved in a model fitted with a formula

n_eta() experimental: The Number of linear predictors in model

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() experimental: 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