/// <summary>
/// Forecasts the series of the fitted model one point ahead.
/// </summary>
/// <param name="input">The input given to the indicator</param>
/// <returns>A new value for this indicator</returns>
protected override decimal ComputeNextValue(IndicatorDataPoint input)
{
_rollingData.Add((double)input.Value);
if (_rollingData.IsReady)
{
var arrayData = _rollingData.ToArray();
arrayData = _diffOrder > 0 ? DifferenceSeries(_diffOrder, arrayData, out _diffHeads) : arrayData;
TwoStepFit(arrayData);
double summants = 0;
if (_arOrder > 0)
{
for (var i = 0; i < _arOrder; i++) // AR Parameters
{
summants += ArParameters[i] * arrayData[i];
}
}
if (_maOrder > 0)
{
for (var i = 0; i < _maOrder; i++) // MA Parameters
{
summants += MaParameters[i] * _residuals[_maOrder + i + 1];
}
}
summants += Intercept; // By default equals 0
if (_diffOrder > 0)
{
var dataCast = arrayData.ToList();
dataCast.Insert(0, summants); // Prepends
summants = InverseDifferencedSeries(dataCast.ToArray(), _diffHeads).First(); // Returns disintegrated series
}
return((decimal)summants);
}
return(0m);
}
/// <summary>
/// Get all pivot points, in the order such that first element in collection is the nearest to the present date
/// </summary>
/// <returns>An array of low and high pivot points. Ordered by time in descending order.</returns>
/// <remarks>Returned array can be empty if no points have been registered yet/</remarks>
public PivotPoint[] GetAllPivotPointsArray()
{
// Get all pivot points within rolling wind. collection as an array
return(_windowPivotPoints.ToArray());
}
