Description Usage Arguments Details Value Author(s) References See Also Examples
Given an n-vector y and the model y=m+e, and an m by n "irreducible" matrix amat, test the null hypothesis that the vector m is in the null space of amat.
1 | doubconetest(y, amat, nsim = 1000)
|
y |
a vector of length n |
amat |
an m by n "irreducible" matrix |
nsim |
number of simulations to approximate null distribution – default is 1000, but choose more if a more precise p-value is desired |
The matrix amat defines a polyhedral convex cone of vectors x such that amat%*%x>=0, and also the opposite cone amat%*%x<=0. The linear space C is those x such that amat%*%x=0. The function provides a p-value for the null hypothesis that m=E(y) is in C, versus the alternative that it is in one of the two cones defined by amat.
pval |
The p-value for the test |
p0 |
The least-squares fit under the null hypothesis |
p1 |
The least-squares fit to the "positive" cone |
p2 |
The least-squares fit to the "negative" cone |
Mary C Meyer and Bodhisattva Sen
TBA, Meyer, M.C. (1999) An Extension of the Mixed Primal-Dual Bases Algorithm to the Case of More Constraints than Dimensions, Journal of Statistical Planning and Inference, 81, pp13-31.
1 2 3 4 5 6 7 8 9 10 11 12 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.