GaussianPrediction-class
                        An S4 class to represent analytically computed
                        predictive distributions (conditional on
                        hyperparameters) of an additive GP model
KernelComputer-class    An S4 class to represent input for kernel
                        matrix computations
Prediction-class        An S4 class to represent prior or posterior
                        draws from an additive function distribution.
add_dis_age             Easily add the disease-related age variable to
                        a data frame
add_factor              Easily add a categorical covariate to a data
                        frame
add_factor_crossing     Add a crossing of two factors to a data frame
adjusted_c_hat          Set the GP mean vector, taking TMM or other
                        normalization into account
apply_scaling           Apply variable scaling
as_character            Character representations of different formula
                        objects
create_model            Create a model
create_model.covs_and_comps
                        Parse the covariates and model components from
                        given data and formula
create_model.formula    Create a model formula
create_model.likelihood
                        Parse the response variable and its likelihood
                        model
create_model.options    Parse the given modeling options
create_model.prior      Parse given prior
create_plot_df          Helper function for plots
create_scaling          Create a standardizing transform
dinvgamma_stanlike      Density and quantile functions of the inverse
                        gamma distribution
draw_pred               Draw pseudo-observations from posterior or
                        prior predictive distribution
example_fit             Quick way to create an example lgpfit, useful
                        for debugging
fit_summary             Print a fit summary.
get_draws               Extract parameter draws from lgpfit or stanfit
get_pred                Extract model predictions and function
                        posteriors
kernel                  Compute a kernel matrix (covariance matrix)
lgp                     Main function of the 'lgpr' package
lgpexpr-class           An S4 class to represent an lgp expression
lgpfit-class            An S4 class to represent the output of the
                        'lgp' function
lgpformula-class        An S4 class to represent an lgp formula
lgpmodel-class          An S4 class to represent an additive GP model
lgpr-package            The 'lgpr' package.
lgprhs-class            An S4 class to represent the right-hand side of
                        an lgp formula
lgpscaling-class        An S4 class to represent variable scaling
lgpsim-class            An S4 class to represent a data set simulated
                        using the additive GP formalism
lgpterm-class           An S4 class to represent one formula term
model_summary           Print a model summary.
new_x                   Create test input points for prediction
operations              Operations on formula terms and expressions
plot_api_c              Plot a generated/fit model component
plot_api_g              Plot longitudinal data and/or model fit so that
                        each subject/group has their own panel
plot_components         Visualize all model components
plot_data               Vizualizing longitudinal data
plot_draws              Visualize the distribution of parameter draws
plot_inputwarp          Visualize input warping function with several
                        steepness parameter values
plot_invgamma           Plot the inverse gamma-distribution pdf
plot_pred               Visualizing model predictions or inferred
                        covariate effects
plot_sim                Visualize an lgpsim object (simulated data)
ppc                     Graphical posterior predictive checks
pred                    Posterior predictions and function posteriors
prior_pred              Prior (predictive) sampling
prior_to_num            Convert given prior to numeric format
priors                  Prior definitions
read_proteomics_data    Function for reading the built-in proteomics
                        data
relevances              Assess component relevances
s4_generics             S4 generics for lgpfit, lgpmodel, and other
                        objects
sample_model            Fitting a model
select                  Select relevant components
show                    Printing formula object info using the show
                        generic
sim.create_f            Simulate latent function components for
                        longitudinal data analysis
sim.create_x            Create an input data frame X for simulated data
sim.create_y            Simulate noisy observations
sim.kernels             Compute all kernel matrices when simulating
                        data
simulate_data           Generate an artificial longitudinal data set
split                   Split data into training and test sets
testdata_001            A very small artificial test data, used mostly
                        for unit tests
testdata_002            Medium-size artificial test data, used mostly
                        for tutorials
validate                Validate S4 class objects
var_mask                Variance masking function
warp_input              Input warping function
