rcone: Generate a Cone of Regression Coefficient Vectors

In fungible: Psychometric Functions from the Waller Lab

Generate a Cone of Regression Coefficient Vectors

Description

Compute a cone of regression vectors with a constant R-squared around a target vector.

Usage

rcone(R, Rsq, b, axis1, axis2, deg, Npoints = 360)

Arguments

R	Predictor correlation matrix.
Rsq	Coefficient of determination.
b	Target vector of OLS regression coefficients.
axis1	1st axis of rotation plane.
axis2	2nd axis of rotation plane.
deg	All vectors b.i will be ‘deg’ degrees from b.
Npoints	Number of rotation vectors, default = 360.

Value

b.i	Npoints values of b.i

Author(s)

Niels Waller and Jeff Jones

References

Waller, N. G. & Jones, J. A. (2011). Investigating the performance of alternate regression weights by studying all possible criteria in regression models with a fixed set of predictors. Psychometrika, 76, 410-439.

Examples

R <- matrix(.5, 4, 4)
diag(R) <- 1

Npoints <- 1000
Rsq <- .40
NumDeg <- 20
V <- eigen(R)$vectors

## create b parallel to v[,3]
## rotate in the 2 - 4 plane
b <- V[,3]
bsq <- t(b) %*% R %*% b 
b <- b * sqrt(Rsq/bsq)                
b.i <- rcone(R, Rsq,b, V[,2], V[,4], deg = NumDeg, Npoints)

t(b.i[,1]) %*% R %*% b.i[,1]
t(b.i[,25]) %*% R %*% b.i[,25]

fungible documentation built on May 29, 2024, 8:28 a.m.