NAG CL Interface
g02gkc (glm_​constrain)

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

1: $\mathbf{ip}$ – Integer Input

On entry: the number of terms in the linear model, $p$.

Constraint: $\mathbf{ip}\ge 1$.

2: $\mathbf{nclin}$ – Integer Input

On entry: the number of constraints to be imposed on the arguments, $n_c$.

Constraint: $0<\mathbf{nclin}<\mathbf{ip}$.

3: $\mathbf{v}\left[\mathbf{ip}\times \mathbf{tdv}\right]$ – const double Input

Note: the $(i,j)$th element of the matrix $V$ is stored in $\mathbf{v}\left[(i-1)\times \mathbf{tdv}+j-1\right]$.

On entry: v as returned by g02gac, g02gbc, g02gcc or g02gdc.

4: $\mathbf{tdv}$ – Integer Input

On entry: the stride separating matrix column elements in the array v.

Constraint: $\mathbf{tdv}\ge \mathbf{ip}+6$.

tdv should be as supplied to g02gac, g02gbc, g02gcc or g02gdc.

5: $\mathbf{c}\left[\mathbf{ip}\times \mathbf{tdc}\right]$ – const double Input

Note: the $(i,j)$th element of the matrix $C$ is stored in $\mathbf{c}\left[(i-1)\times \mathbf{tdc}+j-1\right]$.

On entry: the nclin constraints stored by column, i.e., the $i$th constraint is stored in the $i$th column of c.

6: $\mathbf{tdc}$ – Integer Input

On entry: the stride separating matrix column elements in the array c.

Constraint: $\mathbf{tdc}\ge \mathbf{nclin}$.

7: $\mathbf{b}\left[\mathbf{ip}\right]$ – double Input/Output

On entry: the parameter estimates computed by using the singular value decomposition, ${\hat{\beta }}_{svd}$.

On exit: the parameter estimates of the arguments with the constraints imposed, ${\hat{\beta }}_c$.

8: $\mathbf{scale}$ – double Input

On entry: the estimate of the scale argument.

For results from g02gac and g02gdc then scale is the scale argument, for the model ${\sigma }^2$ and ${\hat{\nu }}^{\mathrm{-1}}$ respectively.

For results from g02gbc and g02gcc then scale should be set to 1.0.

Constraint: $\mathbf{scale}>0.0$.

9: $\mathbf{se}\left[\mathbf{ip}\right]$ – double Output

On exit: the standard error of the parameter estimates in b.

10: $\mathbf{cov}\left[\left(\mathbf{ip}\right)\times (\mathbf{ip}+1)/2\right]$ – double Output

On exit: the upper triangular part of the variance-covariance matrix of the ip parameter estimates given in b. They are stored packed by column, i.e., the covariance between the parameter estimate given in $\mathbf{b}\left[\mathit{i}\right]$ and the parameter estimate given in $\mathbf{b}\left[\mathit{j}\right]$, $\mathit{j}\ge \mathit{i}$, is stored in $\mathbf{cov}\left[\mathit{j}(\mathit{j}+1)/2+\mathit{i}\right]$, for $\mathit{i}=0,1,\dots ,\mathbf{ip}-1$ and $\mathit{j}=\mathit{i},\dots ,\mathbf{ip}-1$.

11: $\mathbf{fail}$ – NagError * Input/Output

The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_2_INT_ARG_GE

On entry, $\mathbf{nclin}=⟨\mathit{\text{value}}⟩$ while $\mathbf{ip}=⟨\mathit{\text{value}}⟩$. These arguments must satisfy $\mathbf{nclin}<\mathbf{ip}$.

NE_2_INT_ARG_LT

On entry, $\mathbf{tdc}=⟨\mathit{\text{value}}⟩$ while $\mathbf{nclin}=⟨\mathit{\text{value}}⟩$. These arguments must satisfy $\mathbf{tdc}\ge \mathbf{nclin}$.

On entry, $\mathbf{tdv}=⟨\mathit{\text{value}}⟩$ while $\mathbf{ip}=⟨\mathit{\text{value}}⟩$. These arguments must satisfy $\mathbf{tdv}\ge \mathbf{ip}+6$.

NE_ALLOC_FAIL

Dynamic memory allocation failed.

NE_INT_ARG_LE

On entry, $\mathbf{nclin}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{nclin}>0$.

NE_INT_ARG_LT

On entry, $\mathbf{ip}=⟨\mathit{\text{value}}⟩$.
Constraint: $\mathbf{ip}\ge 1$.

NE_MAT_NOT_FULL_RANK

Matrix c does not give a model of full rank.

NE_REAL_ARG_LE

On entry, scale must not be less than or equal to 0.0: $\mathbf{scale}=⟨\mathit{\text{value}}⟩$.

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results