NAG CL Interface
g13auc (uni_means)
1
Purpose
g13auc calculates the range (or standard deviation) and the mean for groups of successive time series values. It is intended for use in the construction of rangemean plots.
2
Specification
void 
g13auc (Integer n,
const double z[],
Integer m,
Nag_RangeStat rs,
double y[],
double mean[],
NagError *fail) 

The function may be called by the names: g13auc, nag_tsa_uni_means or nag_tsa_mean_range.
3
Description
Let ${Z}_{1},{Z}_{2},\dots ,{Z}_{n}$ denote $n$ successive observations in a time series. The series may be divided into groups of $m$ successive values and for each group the range or standard deviation (depending on a usersupplied option) and the mean are calculated. If $n$ is not a multiple of $m$ then groups of equal size $m$ are found starting from the end of the series of observations provided, and any remaining observations at the start of the series are ignored. The number of groups used, $k$, is the integer part of $n/m$. If you wish to ensure that no observations are ignored then the number of observations, $n$, should be chosen so that $n$ is divisible by $m$.
The mean,
${M}_{i}$, the range,
${R}_{i}$, and the standard deviation,
${S}_{i}$, for the
$i$th group are defined as
and
where
$l=nkm$, the number of observations ignored.
For seasonal data it is recommended that $m$ should be equal to the seasonal period. For nonseasonal data the recommended group size is $8$.
A plot of range against mean or of standard deviation against mean is useful for finding a transformation of the series which makes the variance constant. If the plot appears random or the range (or standard deviation) seems to be constant irrespective of the mean level then this suggests that no transformation of the time series is called for. On the other hand an approximate linear relationship between range (or standard deviation) and mean would indicate that a log transformation is appropriate. Further details may be found in either
Jenkins (1979) or
McLeod (1982).
You have the choice of whether to use the range or the standard deviation as a measure of variability. If the group size is small they are both equally good but if the group size is fairly large (e.g., $m=12$ for monthly data) then the range may not be as good an estimate of variability as the standard deviation.
4
References
Jenkins G M (1979) Practical Experiences with Modelling and Forecasting Time Series GJP Publications, Lancaster
McLeod G (1982) Box–Jenkins in Practice. 1: Univariate Stochastic and Single Output Transfer Function/Noise Analysis GJP Publications, Lancaster
5
Arguments

1:
$\mathbf{n}$ – Integer
Input

On entry: $n$, the number of observations in the time series.
Constraint:
${\mathbf{n}}\ge {\mathbf{m}}$.

2:
$\mathbf{z}\left[{\mathbf{n}}\right]$ – const double
Input

On entry: ${\mathbf{z}}\left[\mathit{t}1\right]$ must contain the $\mathit{t}$th observation ${Z}_{\mathit{t}}$, for $\mathit{t}=1,2,\dots ,n$.

3:
$\mathbf{m}$ – Integer
Input

On entry: $m$, the group size.
Constraint:
${\mathbf{m}}\ge 2$.

4:
$\mathbf{rs}$ – Nag_RangeStat
Input

On entry: indicates whether ranges or standard deviations are to be calculated.
 ${\mathbf{rs}}=\mathrm{Nag\_UseRange}$
 Ranges are calculated.
 ${\mathbf{rs}}=\mathrm{Nag\_UseSD}$
 Standard deviations are calculated.
Constraint:
${\mathbf{rs}}=\mathrm{Nag\_UseRange}$ or $\mathrm{Nag\_UseSD}$.

5:
$\mathbf{y}\left[\mathit{dim}\right]$ – double
Output

On exit:
${\mathbf{y}}\left[\mathit{i}1\right]$ contains the range or standard deviation, as determined by
rs, of the
$\mathit{i}$th group of observations, for
$\mathit{i}=1,2,\dots ,k$.

6:
$\mathbf{mean}\left[\mathit{dim}\right]$ – double
Output

On exit: ${\mathbf{mean}}\left[\mathit{i}1\right]$ contains the mean of the $\mathit{i}$th group of observations, for $\mathit{i}=1,2,\dots ,k$.

7:
$\mathbf{fail}$ – 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_ALLOC_FAIL

Dynamic memory allocation failed.
See
Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
 NE_BAD_PARAM

On entry, argument $\u2329\mathit{\text{value}}\u232a$ had an illegal value.
 NE_INT

On entry, ${\mathbf{m}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{m}}\ge 2$.
 NE_INT_2

On entry, ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$ and ${\mathbf{m}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{n}}\ge {\mathbf{m}}$.
 NE_INTERNAL_ERROR

An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact
NAG for assistance.
See
Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
 NE_NO_LICENCE

Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library CL Interface for further information.
7
Accuracy
The computations are believed to be stable.
8
Parallelism and Performance
g13auc is not threaded in any implementation.
The time taken by g13auc is approximately proportional to $n$.
10
Example
The following program produces the statistics for a rangemean plot for a series of $100$ observations divided into groups of $8$.
10.1
Program Text
10.2
Program Data
10.3
Program Results