coef.estimate {BGGM}

Compute Regression Parameters for estimate Objects

Description

There is a direct correspondence between the inverse covariance matrix and multiple regression (Kwan 2014; Stephens 1998). This readily allows for converting the GGM parameters to regression coefficients. All data types are supported.

Usage

## S3 method for class 'estimate'
coef(object, iter = NULL, progress = TRUE, ...)

Arguments

object

An Object of class estimate

iter

Number of iterations (posterior samples; defaults to the number in the object).

progress

Logical. Should a progress bar be included (defaults to TRUE) ?

...

Currently ignored.

Value

An object of class coef, containting two lists.

• betas A list of length p, each containing a p - 1 by iter matrix of posterior samples

• object An object of class estimate (the fitted model).

References

Kwan CC (2014). “A regression-based interpretation of the inverse of the sample covariance matrix.” Spreadsheets in Education, 7(1), 4613.

Stephens G (1998). “On the Inverse of the Covariance Matrix in Portfolio Analysis.” The Journal of Finance, 53(5), 1821–1827.

Examples

# note: iter = 250 for demonstrative purposes

#########################
### example 1: binary ###
#########################
# data
Y = matrix( rbinom(100, 1, .5), ncol=4)

# fit model
fit <- estimate(Y, type = "binary",
                iter = 250,
                progress = TRUE)

# summarize the partial correlations
reg <- coef(fit, progress = FALSE)

# summary
summ <- summary(reg)

summ