4 writes to _alpha
Microsoft.ML.TimeSeries (4)
AdaptiveSingularSpectrumSequenceModeler.cs (4)
270
_alpha
= new Single[windowSize - 1];
322
_alpha
= new Single[_windowSize - 1];
387
_alpha
= ctx.Reader.ReadFloatArray();
1292
_alpha
= new Single[_windowSize - 1];
26 references to _alpha
Microsoft.ML.TimeSeries (26)
AdaptiveSingularSpectrumSequenceModeler.cs (26)
323
Array.Copy(model.
_alpha
,
_alpha
, _windowSize - 1);
388
_host.CheckDecode(Utils.Size(
_alpha
) == _windowSize - 1);
420
Array.Copy(
_alpha
, _info.AutoRegressiveCoefficients, _windowSize - 1);
459
_host.Assert(Utils.Size(
_alpha
) == _windowSize - 1);
494
ctx.Writer.WriteSingleArray(
_alpha
);
839
if (Utils.Size(
_alpha
) == 1)
842
_info.RootsBeforeStabilization = new[] { new Complex(
_alpha
[0], 0) };
844
if (
_alpha
[0] > 1)
845
_alpha
[0] = 1;
846
else if (
_alpha
[0] < -1)
847
_alpha
[0] = -1;
852
_info.RootsAfterStabilization = new[] { new Complex(
_alpha
[0], 0) };
855
_info.ExponentialTrendFactor = Math.Abs(
_alpha
[0]);
874
coeff[i] = -
_alpha
[i];
1084
_alpha
[i] = (Single)(-coeff[i]);
1148
_nextPrediction += _state[i] *
_alpha
[i];
1151
_nextPrediction += _state[_windowSize - 2] *
_alpha
[_windowSize - 2];
1349
_alpha
[i] = _xSmooth[i] / (1 - nu);
1369
ComputeNoiseMoments(dataArray, signal,
_alpha
, out _observationNoiseVariance, out _autoregressionNoiseVariance,
1398
_nextPrediction += _state[i - 1] *
_alpha
[i - 1];
1406
Array.Copy(
_alpha
, _info.AutoRegressiveCoefficients, _windowSize - 1);
1442
resEditor.Values[i] += _state[j] *
_alpha
[k];
1445
resEditor.Values[i] += resEditor.Values[j] *
_alpha
[k];
1457
lastCol.AddLast(
_alpha
[_windowSize - 2]);
1464
temp +=
_alpha
[j] * lastCol[j];