Esempio n. 1
0
        //Methods
        /// <summary>
        /// Adds new value to stored time series
        /// </summary>
        /// <param name="nextValue">Next time series value</param>
        public void AddNextValue(double nextValue)
        {
            //Affect next value to existing averages
            Parallel.For(0, _subIntervalLengthCollection.Count, _subIntervalIdx =>
            {
                int intervalLength = _subIntervalLengthCollection[_subIntervalIdx];
                RescalledRange intervalRescalledRange = new RescalledRange(intervalLength);
                for (int valueIdx = (_valueCollection.Count - intervalLength) + 1; valueIdx < _valueCollection.Count; valueIdx++)
                {
                    intervalRescalledRange.AddValue(_valueCollection[valueIdx]);
                }
                intervalRescalledRange.AddValue(nextValue);
                _avgCollection[_subIntervalIdx].AddSampleValue(intervalRescalledRange.Compute());
            });
            //Add new value
            _valueCollection.Add(nextValue);
            _subIntervalLengthCollection.Add(_valueCollection.Count);
            _avgCollection.Add(new WeightedAvg());
            RescalledRange fullRescalledRange = new RescalledRange(_valueCollection.Count);

            foreach (double value in _valueCollection)
            {
                fullRescalledRange.AddValue(value);
            }
            _avgCollection[_avgCollection.Count - 1].AddSampleValue(fullRescalledRange.Compute());
            return;
        }
Esempio n. 2
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        /// <summary>
        /// Computes Hurst exponent estimation for next hypothetical value in time series.
        /// Function does not change the instance, it is a simulation only.
        /// </summary>
        /// <returns>Resulting linear fit object</returns>
        public LinearFit ComputeNext(double simValue)
        {
            //Affect new value to existing averages
            double[] avgValues = new double[_avgCollection.Count];
            Parallel.For(0, _subIntervalLengthCollection.Count, _subIntervalIdx =>
            {
                int intervalLength = _subIntervalLengthCollection[_subIntervalIdx];
                RescalledRange intervalRescalledRange = new RescalledRange(intervalLength);
                for (int valueIdx = (_valueCollection.Count - intervalLength) + 1; valueIdx < _valueCollection.Count; valueIdx++)
                {
                    intervalRescalledRange.AddValue(_valueCollection[valueIdx]);
                }
                intervalRescalledRange.AddValue(simValue);
                avgValues[_subIntervalIdx] = _avgCollection[_subIntervalIdx].SimulateNext(intervalRescalledRange.Compute());
            });
            //Add updated existing points
            LinearFit linFit = new LinearFit();

            for (int i = 0; i < _avgCollection.Count; i++)
            {
                double x   = Math.Log(_subIntervalLengthCollection[i]);
                double avg = avgValues[i];
                double y   = 0;
                if (avg != 0)
                {
                    y = Math.Log(avg);
                }
                linFit.AddSamplePoint(x, y);
            }
            //Return
            return(linFit);
        }
Esempio n. 3
0
 /// <summary>
 /// Creates an initialized instance
 /// </summary>
 /// <param name="timeSeries">Time series data</param>
 public HurstExpEstim(IEnumerable <double> timeSeries)
 {
     _valueCollection = timeSeries.ToList();
     //Check time series length
     if (_valueCollection.Count < MinSubIntervalLength + 1)
     {
         throw new ArgumentException($"Time series is too short. Minimal length is {MinSubIntervalLength + 1}", "timeSeries");
     }
     //Subintervals
     _subIntervalLengthCollection = new List <int>((_valueCollection.Count - MinSubIntervalLength) + 1);
     for (int i = 0, length = MinSubIntervalLength; length <= _valueCollection.Count; i++, length++)
     {
         _subIntervalLengthCollection.Add(length);
     }
     _avgCollection = new List <WeightedAvg>(_subIntervalLengthCollection.Count);
     for (int i = 0; i < _subIntervalLengthCollection.Count; i++)
     {
         _avgCollection.Add(new WeightedAvg());
     }
     Parallel.For(0, _subIntervalLengthCollection.Count, _subIntervalIdx =>
     {
         int intervalLength            = _subIntervalLengthCollection[_subIntervalIdx];
         RescalledRange rescalledRange = new RescalledRange(intervalLength);
         for (int startIdx = 0; startIdx <= _valueCollection.Count - intervalLength; startIdx++)
         {
             rescalledRange.Reset();
             for (int valueSubIdx = 0, timeSeriesIdx = startIdx; valueSubIdx < intervalLength; valueSubIdx++, timeSeriesIdx++)
             {
                 rescalledRange.AddValue(_valueCollection[timeSeriesIdx]);
             }
             _avgCollection[_subIntervalIdx].AddSampleValue(rescalledRange.Compute());
         }
     });
     return;
 }