NAG FL Interface
g02ldf (pls_​pred)

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

1: $\mathbf{ip}$ – Integer Input

On entry: the number of predictor variables in the fitted model. ip must take the same value as that supplied to g02laf or g02lbf to fit the model.

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

2: $\mathbf{my}$ – Integer Input

On entry: the number of response variables in the fitted model. my must take the same value as that supplied to g02laf or g02lbf to fit the model.

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

3: $\mathbf{orig}$ – Integer Input

On entry: indicates how parameter estimates are supplied.

$\mathbf{orig}=1$

Parameter estimates are for the original data.

$\mathbf{orig}=-1$

Parameter estimates are for the centred, and possibly scaled, data.

Constraint: $\mathbf{orig}=-1$ or $1$.

4: $\mathbf{xbar}\left(\mathbf{ip}\right)$ – Real (Kind=nag_wp) array Input

On entry: if $\mathbf{orig}=-1$, xbar must contain mean values of predictor variables in the model; otherwise xbar is not referenced.

5: $\mathbf{ybar}\left(\mathbf{my}\right)$ – Real (Kind=nag_wp) array Input

On entry: if $\mathbf{orig}=-1$, ybar must contain the mean value of each response variable in the model; otherwise ybar is not referenced.

6: $\mathbf{iscale}$ – Integer Input

On entry: if $\mathbf{orig}=-1$, iscale must take the value supplied to either g02laf or g02lbf; otherwise iscale is not referenced.

Constraint: if $\mathbf{orig}=-1$, $\mathbf{iscale}=-1$, $1$ or $2$.

7: $\mathbf{xstd}\left(\mathbf{ip}\right)$ – Real (Kind=nag_wp) array Input

On entry: if $\mathbf{orig}=-1$ and $\mathbf{iscale}\ne -1$, xstd must contain the scalings of predictor variables in the model as returned from either g02laf or g02lbf; otherwise xstd is not referenced.

8: $\mathbf{ystd}\left(\mathbf{my}\right)$ – Real (Kind=nag_wp) array Input

On entry: if $\mathbf{orig}=-1$ and $\mathbf{iscale}\ne -1$, ystd must contain the scalings of response variables as returned from either g02laf or g02lbf; otherwise ystd is not referenced.

9: $\mathbf{b}\left(\mathbf{ldb},\mathbf{my}\right)$ – Real (Kind=nag_wp) array Input

On entry: if $\mathbf{orig}=-1$, b must contain the parameter estimate for the centred, and possibly scaled, data as returned by g02lcf; otherwise b must contain the parameter estimates for the original data as returned by g02lcf.

10: $\mathbf{ldb}$ – Integer Input

On entry: the first dimension of the array b as declared in the (sub)program from which g02ldf is called. If $\mathbf{orig}=-1$, ldb must be at least ip; otherwise b also contains the estimate for the intercept parameter and consequently ldb must be at least $1+\mathbf{ip}$.

Constraints:

• if $\mathbf{orig}=-1$, $\mathbf{ldb}\ge \mathbf{ip}$;
• if $\mathbf{orig}=1$, $\mathbf{ldb}\ge 1+\mathbf{ip}$.

11: $\mathbf{n}$ – Integer Input

On entry: $n$, the number of observations in the test data $Z$.

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

12: $\mathbf{mz}$ – Integer Input

On entry: the number of available predictor variables in the test data.

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

13: $\mathbf{isz}\left(\mathbf{mz}\right)$ – Integer array Input

On entry: indicates which predictor variables are to be included in the model. Predictor variables included from z must be in the same order as those included in the fitted model.

If $\mathbf{isz}\left(\mathit{j}\right)=1$, the $\mathit{j}$th predictor variable is included in the model, for $\mathit{j}=1,2,\dots ,\mathbf{mz}$, otherwise $\mathbf{isz}\left(j\right)=0$.

Constraints:

• $\mathbf{isz}\left(\mathit{j}\right)=0\text{ or }1$, for $\mathit{j}=1,2,\dots ,\mathbf{mz}$;
• ${\sum }_j\mathbf{isz}\left(j\right)=\mathbf{ip}$.

14: $\mathbf{z}\left(\mathbf{ldz},\mathbf{mz}\right)$ – Real (Kind=nag_wp) array Input

On entry: $\mathbf{z}\left(\mathit{i},\mathit{j}\right)$ contains the $\mathit{i}$th observation on the $\mathit{j}$th available predictor variable, for $\mathit{i}=1,2,\dots ,\mathbf{n}$ and $\mathit{j}=1,2,\dots ,\mathbf{mz}$.

15: $\mathbf{ldz}$ – Integer Input

On entry: the first dimension of the array z as declared in the (sub)program from which g02ldf is called.

Constraint: $\mathbf{ldz}\ge \mathbf{n}$.

16: $\mathbf{yhat}\left(\mathbf{ldyhat},\mathbf{my}\right)$ – Real (Kind=nag_wp) array Output

On exit: $\mathbf{yhat}\left(i,j\right)$ contains the $i$th predicted value of the $j$th $y$-variable in the model.

17: $\mathbf{ldyhat}$ – Integer Input

On entry: the first dimension of the array yhat as declared in the (sub)program from which g02ldf is called.

Constraint: $\mathbf{ldyhat}\ge \mathbf{n}$.

18: $\mathbf{ifail}$ – Integer Input/Output

On entry: ifail must be set to $0$, $-1$ or $1$ to set behaviour on detection of an error; these values have no effect when no error is detected.

A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $-1$ means that an error message is printed while a value of $1$ means that it is not.

If halting is not appropriate, the value $-1$ or $1$ is recommended. If message printing is undesirable, then the value $1$ is recommended. Otherwise, the value $0$ is recommended. When the value $-\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.

On exit: $\mathbf{ifail}=\mathbf{0}$ unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

$\mathbf{ifail}=1$

On entry, $\mathbf{ip}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{ip}>1$.

On entry, $\mathbf{iscale}=〈\mathit{\text{value}}〉$.
Constraint: if $\mathbf{orig}=-1$, $\mathbf{iscale}=-1$, $1$ or $2$.

On entry, $\mathbf{isz}\left(〈\mathit{\text{value}}〉\right)=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{isz}\left(j\right)=0$ or $1$.

On entry, $\mathbf{my}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{my}\ge 1$.

On entry, $\mathbf{n}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{n}\ge 1$.

On entry, $\mathbf{orig}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{orig}=-1$ or $1$.

$\mathbf{ifail}=2$

On entry, $\mathbf{ldb}=〈\mathit{\text{value}}〉$ and $\mathbf{ip}=〈\mathit{\text{value}}〉$.
Constraint: if $\mathbf{orig}=-1$, $\mathbf{ldb}\ge \mathbf{ip}$.

On entry, $\mathbf{ldb}=〈\mathit{\text{value}}〉$ and $\mathbf{ip}+1=〈\mathit{\text{value}}〉$.
Constraint: if $\mathbf{orig}=1$, $\mathbf{ldb}\ge 1+\mathbf{ip}$.

On entry, $\mathbf{ldyhat}=〈\mathit{\text{value}}〉$ and $\mathbf{n}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{ldyhat}\ge \mathbf{n}$.

On entry, $\mathbf{ldz}=〈\mathit{\text{value}}〉$ and $\mathbf{n}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{ldz}\ge \mathbf{n}$.

On entry, $\mathbf{mz}=〈\mathit{\text{value}}〉$ and $\mathbf{ip}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{mz}\ge \mathbf{ip}$.

$\mathbf{ifail}=3$

On entry, the number of elements of isz equal to $1$ is not ip.

$\mathbf{ifail}=-99$

An unexpected error has been triggered by this routine. Please contact NAG.

See Section 7 in the Introduction to the NAG Library FL Interface for further information.

$\mathbf{ifail}=-399$

Your licence key may have expired or may not have been installed correctly.

See Section 8 in the Introduction to the NAG Library FL Interface for further information.

$\mathbf{ifail}=-999$

Dynamic memory allocation failed.

See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results