Integer, Intent (In)	::	n, nfac, isf(nfac), lfac(nfac), ifac(ldf,nfac), ldf, maxt
Integer, Intent (Inout)	::	ncells, icount(maxt), ifail
Integer, Intent (Out)	::	ndim, idim(nfac), iwk(2*nfac)
Real (Kind=nag_wp), Intent (In)	::	y(n), wt(*)
Real (Kind=nag_wp), Intent (Inout)	::	table(maxt), auxt(*)
Character (1), Intent (In)	::	stat, update, weight

C Header Interface

#include <nag.h>

void

g11baf_ (const char *stat, const char *update, const char *weight, const Integer *n, const Integer *nfac, const Integer isf[], const Integer lfac[], const Integer ifac[], const Integer *ldf, const double y[], const double wt[], double table[], const Integer *maxt, Integer *ncells, Integer *ndim, Integer idim[], Integer icount[], double auxt[], Integer iwk[], Integer *ifail, const Charlen length_stat, const Charlen length_update, const Charlen length_weight)

The routine may be called by the names g11baf or nagf_contab_tabulate_stat.

3 Description

A dataset may include both classification variables and general variables. The classification variables, known as factors, take a small number of values known as levels. For example, the factor sex would have the levels male and female. These can be coded as

1

and

2

respectively. Given several factors, a multi-way table can be constructed such that each cell of the table represents one level from each factor. For example, the two factors sex and habitat, habitat having three levels (inner-city, suburban and rural) define the

2 \times 3

contingency table

	Habitat
Sex	Inner-city	Suburban	Rural
Male
Female

For each cell statistics can be computed. If a third variable in the dataset was age, then for each cell the average age could be computed:

	Habitat
Sex	Inner-city	Suburban	Rural
Male	25.5	30.3	35.6
Female	23.2	29.1	30.4

That is the average age for all observations for males living in rural areas is

35.6

. Other statistics can also be computed: the number of observations, the total, the variance, the largest value and the smallest value.

g11baf computes a table for one of the selected statistics. The factors have to be coded with levels

1, 2, \dots

. Weights can be used to eliminate values from the calculations, e.g., if they represent ‘missing values’. There is also the facility to update an existing table with the addition of new observations.

4 References

John J A and Quenouille M H (1977) Experiments: Design and Analysis Griffin

Kendall M G and Stuart A (1969) The Advanced Theory of Statistics (Volume 1) (3rd Edition) Griffin

West D H D (1979) Updating mean and variance estimates: An improved method Comm. ACM 22 532–555

5 Arguments

1: $stat$ – Character(1) Input

On entry: indicates which statistic is to be computed for the table cells.

$stat ='N'$: The number of observations for each cell.
$stat ='T'$: The total for the variable in y for each cell.
$stat ='A'$: The average (mean) for the variable in y for each cell.
$stat ='V'$: The variance for the variable in y for each cell.
$stat ='L'$: The largest value for the variable in y for each cell.
$stat ='S'$: The smallest value for the variable in y for each cell.

Constraint:

stat ='N'

'T'

'A'

'V'

'L'

'S'

2: $update$ – Character(1) Input

On entry: indicates if an existing table is to be updated by further observation.

$update ='I'$: The table cells will be initialized to zero before tabulations take place.
$update ='U'$: The table input in table will be updated. The arguments ncells, table, icount and auxt must remain unchanged from the previous call to g11baf.

Constraint:

update ='I'

'U'

3: $weight$ – Character(1) Input

On entry: indicates if weights are to be used.

$weight ='U'$: Weights are not used and unit weights are assumed.
$weight ='W'$ or $'V'$: Weights are used and must be supplied in wt. The only difference between $weight ='W'$ and $weight ='V'$ is if the variance is computed.
$weight ='W'$: The divisor for the variance is the sum of the weights minus one and if $weight ='V'$ , the divisor is the number of observations with nonzero weights minus one. The former is useful if the weights represent the frequency of the observed values.

stat ='T'

'A'

, the weighted total or mean is computed respectively.

stat ='N'

'L'

'S'

, the only effect of weights is to eliminate values with zero weights from the computations.

Constraint:

weight ='U'

'V'

'W'

4: $n$ – Integer Input

On entry: the number of observations.

Constraint:

n \geq 2

5: $nfac$ – Integer Input

On entry: the number of classifying factors in ifac.

Constraint:

nfac \geq 1

6: $isf (nfac)$ – Integer array Input

On entry: indicates which factors in ifac are to be used in the tabulation.

isf (i) > 0

the

i

th factor in ifac is included in the tabulation.

Note that if

isf (i) \leq 0

, for

i = 1, 2, \dots, nfac

then the statistic for the whole sample is calculated and returned in a

1 \times 1

table.

7: $lfac (nfac)$ – Integer array Input

On entry: the number of levels of the classifying factors in ifac.

Constraint: if

isf (i) > 0

lfac (i) \geq 2

, for

i = Ai, \dots, Ai

8: $ifac (ldf, nfac)$ – Integer array Input

On entry: the nfac coded classification factors for the n observations.

Constraint:

1 \leq ifac (i, j) \leq lfac (j)

, for

i = 1, 2, \dots, n

and

j = 1, 2, \dots, nfac

9: $ldf$ – Integer Input

On entry: the first dimension of the array ifac as declared in the (sub)program from which g11baf is called.

Constraint:

ldf \geq n

10: $y (n)$ – Real (Kind=nag_wp) array Input

On entry: the variable to be tabulated. If

stat ='N'

, y is not referenced.

11: $wt (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array wt must be at least

n

weight ='W'

'V'

, and at least

1

otherwise.

On entry: if

weight ='W'

'V'

, wt must contain the n weights. Otherwise wt is not referenced.

Constraint: if

weight ='W'

'V'

wt (i) \geq 0.0

, for

i = Ai, \dots, Ai

12: $table (maxt)$ – Real (Kind=nag_wp) array Input/Output

On entry: if

update ='U'

, table must be unchanged from the previous call to g11baf, otherwise table need not be set.

On exit: the computed table. The ncells cells of the table are stored so that for any two factors the index relating to the factor referred to later in lfac and ifac changes faster. For further details see Section 9.

13: $maxt$ – Integer Input

On entry: the maximum size of the table to be computed.

Constraint:

maxt \geq

product of the levels of the factors included in the tabulation.

14: $ncells$ – Integer Input/Output

On entry: if

update ='U'

, ncells must be unchanged from the previous call to g11baf, otherwise ncells need not be set.

On exit: the number of cells in the table.

15: $ndim$ – Integer Output

On exit: the number of factors defining the table.

16: $idim (nfac)$ – Integer array Output

On exit: the first ndim elements contain the number of levels for the factors defining the table.

17: $icount (maxt)$ – Integer array Input/Output

On entry: if

update ='U'

, icount must be unchanged from the previous call to g11baf, otherwise icount need not be set.

On exit: a table containing the number of observations contributing to each cell of the table, stored identically to table. Note if

stat ='N'

this is the same as is returned in table.

18: $auxt (*)$ – Real (Kind=nag_wp) array Input/Output

Note: the dimension of the array auxt must be at least

maxt

stat ='A'

and at least

2 \times maxt

stat ='V'

On entry: if

update ='U'

, auxt must be unchanged from the previous call to g11baf, otherwise auxt need not be set.

On exit: if

stat ='A'

'V'

, the first ncells values hold the table containing the sum of the weights for the observations contributing to each cell, stored identically to table.

stat ='V'

, the second set of ncells values hold the table of cell means. Otherwise auxt is not referenced.

19: $iwk (2 \times nfac)$ – Integer array Workspace

20: $ifail$ – Integer Input/Output

On entry: ifail must be set to

0

−1

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

1

is recommended. If message printing is undesirable, then the value

1

is recommended. Otherwise, the value

0

is recommended. When the value $- 1$ or $1$ is used it is essential to test the value of ifail on exit.

On exit:

ifail = 0

unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

−1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $ldf = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $ldf \geq n$ .

On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 2$ .

On entry, $nfac = ⟨ value ⟩$ .
Constraint: $nfac \geq 1$ .

On entry, $stat = ⟨ value ⟩$ .
Constraint: $stat ='N'$ , $'T'$ , $'A'$ , $'V'$ , $'L'$ or $'S'$ .

On entry, $update = ⟨ value ⟩$ .
Constraint: $update ='I'$ or $'U'$ .

On entry, $weight = ⟨ value ⟩$ .
Constraint: $weight ='U'$ , $'V'$ or $'W'$ .

$ifail = 2$: On entry, $i = ⟨ value ⟩$ , $j = ⟨ value ⟩$ , $lfac (j) = ⟨ value ⟩$ and $ifac (i, j) = ⟨ value ⟩$ .
Constraint: $ifac (i, j) \leq lfac (j)$ .

On entry, $i = ⟨ value ⟩$ , $j = ⟨ value ⟩$ and $ifac (i, j) = ⟨ value ⟩$ .
Constraint: $ifac (i, j) > 0$ .

On entry, $i = ⟨ value ⟩$ and $lfac (i) = ⟨ value ⟩$ .
On entry, $lfac (i) > 2$ .

On entry, $i = ⟨ value ⟩$ and $wt (i) = ⟨ value ⟩$ .
Constraint: $wt (i) \geq 0.0$ .

On entry, $maxt = ⟨ value ⟩$ and minimum value for $maxt = ⟨ value ⟩$ .
Constraint: $maxt \geq product$ of the levels of the factors included in the tabulation.

$ifail = 3$: The variance divisor $\leq 0.0$ .

$ifail = 4$: auxt has changed between calls.

auxt or table has changed between calls.

ncells has changed between calls.

$ifail = - 99$: 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.

$ifail = - 399$: 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.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

Only applicable when

stat ='V'

. In this case a one pass algorithm is used as described by West (1979).

8 Parallelism and Performance

g11baf is not threaded in any implementation.

9 Further Comments

The tables created by g11baf and stored in table, icount and, depending on stat, also in auxt are stored in the following way. Let there be

n

factors defining the table with factor

k

having

l_{k}

levels, then the cell defined by the levels

i_{1}

i_{2}, \dots, i_{n}

of the factors is stored in the

m

th cell given by

m = 1 + \sum_{k = 1}^{n} [(i_{k} - 1) c_{k}],

where

c_{j} = \prod_{k = j + 1}^{n} l_{k}

, for

j = 1, 2, \dots, n - 1

and

c_{n} = 1

10 Example

The data, given by John and Quenouille (1977), is for a

3 \times 6

factorial experiment in

3

blocks of

18

units. The data is input in the order, blocks, factor with

3

levels, factor with

6

levels, yield. The

3 \times 6

table of treatment means for yield over blocks is computed and printed.

g11ba: FL CL CPP AD

NAG FL Interfaceg11baf (tabulate_​stat)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
g11baf (tabulate_stat)