Package index • multilevelcoda

All functions

VarCorr(<brmcoda>): Extract Variance and Correlation Components
as.data.frame(<complr>) as.matrix(<complr>): Extract amounts and compositions in conventional formats as data.frames, matrices, or arrays.
bayes_factor(<brmcoda>): Bayes Factors from Marginal Likelihoods
brmcoda(): Fit Bayesian generalised (non-)linear multilevel compositional model via full Bayesian inference
bsub(): Between-person Simple Substitution
bsubmargin(): Between-person Average Substitution
build.base(): Build Base Pairwise Substitution
build.rg(): Reference Grid for substitution model.
build.sbp(): Build Sequential Binary Partition
coef(<brmcoda>): Model Coefficients
compilr(): Indices from a (dataset of) Multilevel Composition(s) (deprecated.)
complr(): Indices from a (dataset of) Multilevel Composition(s)
log_posterior(<brmcoda>) nuts_params(<brmcoda>) rhat(<brmcoda>) neff_ratio(<brmcoda>): Extract Diagnostic Quantities from brmsfit Models in brmcoda
variables(<brmcoda>) nvariables(<brmcoda>) niterations(<brmcoda>) nchains(<brmcoda>) ndraws(<brmcoda>): Index brmcoda objects
fitted(<brmcoda>): Expected Values of the Posterior Predictive Distribution
fixef(<brmcoda>): Population-Level Estimates
get-substitution: Substitution analysis helper functions
get_sbp(): Extract Sequential Binary Partition from a complr object.
get_variables(): Extract variable names from an object
is.brmcoda(): Checks if argument is a brmcoda object
is.complr(): Checks if argument is a complr object
is.substitution(): Checks if argument is a substitution object
launch_shinystan(<brmcoda>): Interface to shinystan
loo(<brmcoda>): Efficient approximate leave-one-out cross-validation (LOO)
mcmc_plot(<brmcoda>): MCMC Plots Implemented in bayesplot
mcompd: Multilevel Compositional Data
mean(<complr>): Mean amounts and mean compositions presented in a complr object.
model.frame(<brmcoda>): Extracting the Model Frame from a Formula or Fit from brmcoda object
multilevelcoda_sim(): multilevelcoda Simulation Study Results
nobs(<brmcoda>): Extract Number of Observations from brmcoda object
pairs(<brmcoda>): Create a matrix of output plots from a brmcoda's brmsfit object
pivot_coord(): Estimate pivot balance coordinates
pivot_coord_refit(): Estimate pivot balance coordinates by refitting model.
pivot_coord_rotate(): Estimate pivot balance coordinates by rotating sequential binary partition.
plot(<brmcoda>): Trace and Density Plots for MCMC Draws plot
plot(<substitution>): Substitution Plot
pp_check(<brmcoda>): Posterior Predictive Checks for brmcoda Objects
predict(<brmcoda>): Draws from the Posterior Predictive Distribution
print(<brmcoda>): Print a Summary for a fitted brmsfit model in a brmcoda object
print(<complr>): Print a Summary for a complr object
print(<substitution>): Print a Summary for a substitution object
prior_summary(<brmcoda>): Extract Priors of a brmsfit from a brmcoda object
psub: Possible Pairwise Substitutions
ranef(<brmcoda>): Group-Level Estimates
residuals(<brmcoda>): Posterior Draws of Residuals/Predictive Errors
sbp: Sequential Binary Partition
sim: multilevelcoda Simulation Study results
sub(): Simple Substitution
submargin(): Average Substitution
substitution(): Multilevel Compositional Substitution Analysis
summary(<brmcoda>): Create a Summary of a fitted brmsfit model in a brmcoda object
summary(<complr>): Create a Summary of a complr object
summary(<pivot_coord>): Create a Summary of a fitted brmsfit model from a pivot_coord object
summary(<substitution>): Create a Summary of a Substitution Model represented by a substitution object
update(<brmcoda>): Update brmcoda models
var(<complr>): Variance of compositions presented in a complr object.
vcov(<brmcoda>): Covariance and Correlation Matrix of Population-Level Effects
wsub(): Within-person Simple Substitution
wsubmargin(): Within-person Average Substitution