summary_quantiles: Produce quantile summaries of model posterior samples

Description Usage Arguments Value Author(s) See Also

View source: R/summary_quantiles.R

Description

Inputs MCMC samples for model parameters and constructs c(2.5%,50%,97.5%) quantile summaries.

Usage

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summary_quantiles(model.output, Nfixed, Nrandom, Nsubject, Nsubj.aff = NULL,
  Nmv = 1, Nsession = NULL)

Arguments

model.output

An output object of class within c("dpgrow", "dpgrowmm")

Nfixed

Number of total fixed effects, both time-based and nuisance.

Nrandom

Number of total random effects, both time-based and nuisance, all grouped by subject.

Nsubject

Number of unique subjects (on which repeated measures are observed).

Nsubj.aff

Number of subjects, P.aff, receiving multiple membership effects

Nmv

Number of multivariate MM effects. Defaults to 1 for univariate MM if left blank.

Nsession

Number of multiple membership effects for each entry in "Nmv". May be left blank for univariate MM.

Value

A list object containing quantile summaries for all sampled model parameters.

deviance.summary

vector of length 3 summarizing quantiles for model deviance.

beta.summary

Nfixed x 3 quantile summaries of model fixed effects.

alpha.summary

quantile summary of model global intercept parameter.

bmat.summary

list object of length Nrandom, each cell containing a Nsubject x 3 matrix of by-subject parameter quantile summaries.

tauu.summary

Nmv x 3 quantile summary for prior precision parameters employed for multiple membership random effects. An nty x 3 matrix in the case of nty multiple membership effect terms.

taue.summary

quantile summary for model error precision parameter.

taub

Nrandom x 3 quantile summaries for subject effect precision parameters.

u.summary

S*Nmv x 3 quantile summaries for multiple membership random effect parameters. A list of such matrices in the case of nty multiple membership effect terms.

mm.summary

Nsubj.aff x 3 quantile summaries derived from multiplying the affected subject weight matrix by the multiple membership random effects.

M.summary

quantile summary for number of DP posterior clusters formed.

Dbar

Model fit statistics.

pD

Model fit statistics.

pV

Model fit statistics.

DIC

Model fit statistics.

lpml

Model fit statistics.

Author(s)

Terrance Savitsky tds151@gmail.com

See Also

dpgrowmm, dpgrow


growcurves documentation built on May 2, 2019, 7:03 a.m.