Differences a seasonal or nonseasonal time series.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.0.0

Syntax

C#
[SerializableAttribute]
public class Difference
Visual Basic (Declaration)
<SerializableAttribute> _
Public Class Difference
Visual C++
[SerializableAttribute]
public ref class Difference

Remarks

Class Difference performs m = periods.Length successive backward differences of period s_i = {\rm {periods}} [i - 1] and order d_i = {\rm {orders}} [i - 1] \,\, {\rm{for}} \,\, i = 1, \dots, m on the n = z.Length observations \left\{ Z_t \right\} \,\, {\rm{for}} \,\, t = 1, 2, \dots, n.

Consider the backward shift operator B given by

B^kZ_t = Z_{t-k}

for all k. Then, the backward difference operator with period s is defined by the following:

\Delta _s Z_t  = \left( {1 - B^s } \right)Z_t 
            = Z_t  - Z_{t - s} \,\,\,\,\,\,{\rm{for}}\,s \ge 0

Note that B_sZ_t and \Delta_sZ_t are defined only for t = (s + 1), \dots, n. Repeated differencing with period s is simply

\Delta _s^d Z_t  = \left( {1 - B^s } \right)^d 
            Z_t  = \sum\limits_{j = 0}^d {\frac{{d!}}{{j!\left( {d - j} \right)!}}} 
            \left( { - 1} \right)^j B^{sj} Z_t

where d \ge 0 is the order of differencing. Note that

 \Delta _s^d Z_t

is defined only for t = (sd + 1), \dots, n.

The general difference formula used in the class Difference is given by

W_T = \left\{ \begin{array}{ll} \rm{NaN} & 
            {\rm for}\,\, t = 1, \ldots, n_L  \\ \Delta _{s_1 }^{d_1 } 
            \Delta _{s_2 }^{d2} \ldots \Delta _{s_m }^{d_m } Z_t & {\rm for}\,\, 
            t = n_L  + 1,\ldots, n \end{array} \right.

where n_L represents the number of observations "lost" because of differencing and NaN represents the missing value code. Note that

n_L  = \sum\limits_j {s_j d_j }

A homogeneous, stationary time series can be arrived at by appropriately differencing a homogeneous, nonstationary time series (Box and Jenkins 1976, p. 85). Preliminary application of an appropriate transformation followed by differencing of a series can enable model identification and parameter estimation in the class of homogeneous stationary autoregressive moving average models.

Inheritance Hierarchy

System..::.Object
Imsl.Stat..::.Difference

See Also