coef.cv.rbridge: Extract coefficients from a fitted cv.rbridge object

In rbridge: Restricted Bridge Estimation

Extract coefficients from a fitted cv.rbridge object

Description

Extract original-scale intercept and slope coefficients from a fitted cross-validated cv.rbridge object.

Usage

## S3 method for class 'cv.rbridge'
coef(object, s = c("lambda.1se", "lambda.min"), ...)

Arguments

object	Fitted object returned by cv.rbridge, with p predictors in its training design.
s	Penalty selection, using numeric fitted values or a character name. Numeric values must match object$lambda exactly; no interpolation is used. The character selectors are: "lambda.min" Select the penalty with minimum CV error. "lambda.1se" Select using the historical CV error bars. The default is lambda.1se.
...	Additional arguments accepted for compatibility.

Details

The returned matrix retains its dimensions for a single selected penalty. The defaults differ between coef() and predict(): coefficient extraction uses lambda.1se, whereas response prediction uses lambda.min. Specify the same s in both calls when comparing coefficients and their predictions. Returned slopes are on the original predictor scale; the linear restrictions concern standardized slopes. See rbridge for converting scales before checking restriction residuals.

Value

Numeric matrix with p + 1 rows and one column per selected penalty, even when only one penalty is selected. The first row is (Intercept); subsequent rows are original-scale slopes in the training predictor order.

Author(s)

Bahadir Yuzbasi
Maintainer: Bahadir Yuzbasi [e-mail]

See Also

predict.cv.rbridge, cv.rbridge

Examples

# Reproducible synthetic demonstration: 100 observations, eight predictors.
set.seed(2019)
beta <- c(3, 1.5, 0, 0, 2, 0, 0, 0)
p <- length(beta)
beta <- matrix(beta, nrow = p, ncol = 1)
n <- 100
X <- matrix(rnorm(n * p), nrow = n, ncol = p)
y <- as.numeric(X %*% beta + rnorm(n))
# A user-specified sum of standardized slopes: b[1] + b[2] + b[5] = 6.5.
# This target is illustrative; it is not asserted to equal the generating sum.
R1.mat <- matrix(c(1, 1, 0, 0, 1, 0, 0, 0), nrow = 1)
r1.vec <- matrix(6.5, nrow = 1, ncol = 1)

# Five penalties keep this help example fast; the default is 100.
model1 <- cv.rbridge(X, y, q = 1, R = R1.mat, r = r1.vec, nlambda = 5,
                     nfolds = 3, num_threads = 1)
# A single selected penalty still gives a coefficient matrix.
coefficients <- coef(model1, s = "lambda.min")
coefficients
dim(coefficients)
# The default uses the historical error-bar selector.
coef(model1)

rbridge documentation built on Oct. 13, 2026, 9:08 a.m.