weighting: Computing the weights for different WOCR models.
In xgsu/WOCR: Weighted Orthogonal Components Regression (WOCR) Analysis

Description Usage Arguments Details Value References See Also

Computing the weights for different WOCR models.

1	weighting(lambda, d, gamma, model = "RR.d.lambda", a = 20)

`lambda`	The tuning parameter(s) to be optimized. It is 1-D in models `RR.d.lambda`, `RR.gamma.lambda`, `PCR.d.c`, `PCR.gamma.c` and 2-D in models `PCR.d.a.c` and `PCR.gamma.a.c`.
`d`	The vector of singular values of the design matrix X.
`gamma`	The vector of coefficients, consisting of the inner product of each orthogonal component and the repsonse y.
`model`	Specifies the WOCR model to be fitted. Six choices are possible: `RR.d.lambda`, `RR.gamma.lambda`, `PCR.d.c`, `PCR.gamma.c`, `PCR.d.a.c` and `PCR.gamma.a.c`.
`a`	The fixed shape parameter a in models `PCR.d.c` and `PCR.gamma.c` only. Its default value is 20.

This function computes the weights for each orthogonal component, depending on which WOCR model is used. It is intended for internal use within this package only.

The (p-dimensional) vectir of weights for each component.