summary.var_estimate: Summary Method for 'var_estimate' Objects

In donaldRwilliams/BGGM: Bayesian Gaussian Graphical Models

Summary Method for var_estimate Objects

Description

Summarize the posterior distribution of each partial correlation and regression coefficient with the posterior mean, standard deviation, and credible intervals.

Usage

## S3 method for class 'var_estimate'
summary(object, cred = 0.95, ...)

Arguments

object	An object of class var_estimate
cred	Numeric. The credible interval width for summarizing the posterior distributions (defaults to 0.95; must be between 0 and 1).
...	Currently ignored.

Value

A dataframe containing the summarized posterior distributions, including both the partial correlations and the regression coefficients.

• pcor_results A data frame including the summarized partial correlations

• beta_results A list containing the summarized regression coefficients (one data frame for each outcome)

See Also

var_estimate

Examples

# data
Y <- subset(ifit, id == 1)[,-1]

# fit model with alias (var_estimate also works)
fit <- var_estimate(Y, progress = FALSE)

# summary ('pcor')
print(
summary(fit, cred = 0.95),
param = "pcor",
)


# summary ('beta')
print(
summary(fit, cred = 0.95),
param = "beta",
)

donaldRwilliams/BGGM documentation built on April 17, 2024, 5:52 p.m.