public void CanSample() { var n = new Laplace(); n.Sample(); }
public void CanSampleSequence() { var n = new Laplace(); var ied = n.Samples(); GC.KeepAlive(ied.Take(5).ToArray()); }
public void ValidateDensity(double location, double scale, double x) { var n = new Laplace(location, scale); double expected = Math.Exp(-Math.Abs(x - location)/scale)/(2.0*scale); Assert.AreEqual(expected, n.Density(x)); Assert.AreEqual(expected, Laplace.PDF(location, scale, x)); }
public void ValidateDensityLn(double location, double scale, double x) { var n = new Laplace(location, scale); double expected = -Math.Log(2.0*scale) - (Math.Abs(x - location)/scale); Assert.AreEqual(expected, n.DensityLn(x)); Assert.AreEqual(expected, Laplace.PDFLn(location, scale, x)); }
public void ValidateMean(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(location, n.Mean); }
public void SetScaleFailsWithNegativeScale(double scale) { var n = new Laplace(); Assert.Throws<ArgumentOutOfRangeException>(() => n.Scale = scale); }
public void ValidateEntropy(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(Math.Log(2.0 * Constants.E * scale), n.Entropy); }
public void CanCreateLaplace(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(location, n.Location); Assert.AreEqual(scale, n.Scale); }
public void ValidateVariance(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(2.0 * scale * scale, n.Variance); }
public void ValidateStdDev(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(Constants.Sqrt2 * scale, n.StdDev); }
public void SetScaleFailsWithNegativeScale(double scale) { var n = new Laplace(); Assert.That(() => n.Scale = scale, Throws.ArgumentException); }
public void SetLocationFailsWithNegativeLocation() { var n = new Laplace(); Assert.That(() => n.Location = Double.NaN, Throws.ArgumentException); }
static void Main(string[] args) { var randomGenerator = new Random(); var fundamentalValue = GenerateFunamentalValuePath(SimulationSteps, FundamentalValueInitial, FundamentalValueDrift, FundamentalValueVariance); var fundamentalistScale = 10; var chartistScale = 1.2; var noiseScale = 1; var fundamentalistDistribution = new Laplace(0, fundamentalistScale); fundamentalistDistribution.RandomSource = randomGenerator; var chartistDistribution = new Laplace(0, chartistScale); chartistDistribution.RandomSource = randomGenerator; var noiseDistribution = new Laplace(0, noiseScale); noiseDistribution.RandomSource = randomGenerator; var normal = new Normal(0, 5); _agents = new HetroTradingRulesAgent[NumberOfAgents]; var solver = new Brent(); for (int i = 0; i < NumberOfAgents; i++) { _agents[i] = new HetroTradingRulesAgent(Math.Abs(fundamentalistDistribution.Sample()), Math.Abs(chartistDistribution.Sample()), Math.Abs(noiseDistribution.Sample()), ReferenceAgentTimeHorizon, ReferenceRiskAversionLevel, randomGenerator, solver); _agents[i].StockHeld = (int)Math.Floor(MaxNumberOfStock * randomGenerator.NextDouble()); _agents[i].CashHeld = Math.Round(MaxNumberOfStock * FundamentalValueInitial * randomGenerator.NextDouble(), 2); } Thread.Sleep(1000); var connection = new HubConnection(@"http://*****:*****@"c:\temp\hetroTradingRulesNoiseFundChart.csv"; File.WriteAllLines(outputFile, new string[] { string.Format("{0},{1},{2}", "TimeStep", "Price", "Fundamental") }); for (int i = stepsToFill; i < SimulationSteps - ReferenceAgentTimeHorizon; i++) { var agentIndex = (int)Math.Round((NumberOfAgents - 1) * randomGenerator.NextDouble()); Order order = null; try { order = _agents[agentIndex].GetAction(i, spotPrice, fundamentalValue, noise, _currentLimitOrderBook != null ? _currentLimitOrderBook.BestBidPrice : null, _currentLimitOrderBook != null ? _currentLimitOrderBook.BestAskPrice : null); } catch (Exception e) { System.Console.WriteLine("ERROR: {0}", e.Message); } if (order != null) { order.UserID = agentIndex.ToString(); var r = hub.Invoke<bool>("ProcessOrderInstruction", order, agentIndex.ToString()); r.Wait(); Thread.Sleep(10); if (order.Type == OrderType.MarketOrder) { spotPrice[i] = order.Price; } else if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestAskPrice.HasValue && _currentLimitOrderBook.BestBidPrice.HasValue) { spotPrice[i] = (_currentLimitOrderBook.BestBidPrice.Value + _currentLimitOrderBook.BestAskPrice.Value) / 2; } //else if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestAskPrice.HasValue) //{ // spotPrice[i] = _currentLimitOrderBook.BestAskPrice.Value; //} //else if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestBidPrice.HasValue) //{ // spotPrice[i] = _currentLimitOrderBook.BestBidPrice.Value; //} else { spotPrice[i] = spotPrice[i - 1]; } } else { spotPrice[i] = spotPrice[i - 1]; } File.AppendAllLines(outputFile, new string[] { string.Format("{0},{1},{2}", i, spotPrice[i], fundamentalValue[i]) }); System.Console.WriteLine(string.Format("{0}\t\t{1}",i,spotPrice[i])); } }
public void ValidateCumulativeDistribution(double location, double scale, double x) { var n = new Laplace(location, scale); double expected = 0.5*(1.0 + (Math.Sign(x - location)*(1.0 - Math.Exp(-Math.Abs(x - location)/scale)))); Assert.AreEqual(expected, n.CumulativeDistribution(x)); Assert.AreEqual(expected, Laplace.CDF(location, scale, x)); }
public void ValidateSkewness(double location, double scale) { var n = new Laplace(location, scale); Assert.AreEqual(0.0, n.Skewness); }
public void CanCreateLaplace() { var n = new Laplace(); Assert.AreEqual(0.0, n.Location); Assert.AreEqual(1.0, n.Scale); }
public void ValidateMinimum() { var n = new Laplace(); Assert.AreEqual(Double.NegativeInfinity, n.Minimum); }
public void ValidateToString() { var n = new Laplace(-1d, 2d); Assert.AreEqual("Laplace(μ = -1, b = 2)", n.ToString()); }
public void ValidateMaximum() { var n = new Laplace(); Assert.AreEqual(Double.PositiveInfinity, n.Maximum); }
/// <summary> /// Run example /// </summary> /// <a href="http://en.wikipedia.org/wiki/Laplace_distribution">Laplace distribution</a> public void Run() { // 1. Initialize the new instance of the Laplace distribution class with parameters Location = {0}, Scale = {1} var laplace = new Laplace(0, 1); Console.WriteLine(@"1. Initialize the new instance of the Laplace distribution class with parameters Location = {0}, Scale = {1}", laplace.Location, laplace.Scale); Console.WriteLine(); // 2. Distributuion properties: Console.WriteLine(@"2. {0} distributuion properties:", laplace); // Cumulative distribution function Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", laplace.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000")); // Probability density Console.WriteLine(@"{0} - Probability density at location '0.3'", laplace.Density(0.3).ToString(" #0.00000;-#0.00000")); // Log probability density Console.WriteLine(@"{0} - Log probability density at location '0.3'", laplace.DensityLn(0.3).ToString(" #0.00000;-#0.00000")); // Entropy Console.WriteLine(@"{0} - Entropy", laplace.Entropy.ToString(" #0.00000;-#0.00000")); // Largest element in the domain Console.WriteLine(@"{0} - Largest element in the domain", laplace.Maximum.ToString(" #0.00000;-#0.00000")); // Smallest element in the domain Console.WriteLine(@"{0} - Smallest element in the domain", laplace.Minimum.ToString(" #0.00000;-#0.00000")); // Mean Console.WriteLine(@"{0} - Mean", laplace.Mean.ToString(" #0.00000;-#0.00000")); // Median Console.WriteLine(@"{0} - Median", laplace.Median.ToString(" #0.00000;-#0.00000")); // Mode Console.WriteLine(@"{0} - Mode", laplace.Mode.ToString(" #0.00000;-#0.00000")); // Variance Console.WriteLine(@"{0} - Variance", laplace.Variance.ToString(" #0.00000;-#0.00000")); // Standard deviation Console.WriteLine(@"{0} - Standard deviation", laplace.StdDev.ToString(" #0.00000;-#0.00000")); // Skewness Console.WriteLine(@"{0} - Skewness", laplace.Skewness.ToString(" #0.00000;-#0.00000")); Console.WriteLine(); // 3. Generate 10 samples of the Laplace distribution Console.WriteLine(@"3. Generate 10 samples of the Laplace distribution"); for (var i = 0; i < 10; i++) { Console.Write(laplace.Sample().ToString("N05") + @" "); } Console.WriteLine(); Console.WriteLine(); // 4. Generate 100000 samples of the Laplace(0, 1) distribution and display histogram Console.WriteLine(@"4. Generate 100000 samples of the Laplace(0, 1) distribution and display histogram"); var data = new double[100000]; for (var i = 0; i < data.Length; i++) { data[i] = laplace.Sample(); } ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 5. Generate 100000 samples of the Laplace(0, 4) distribution and display histogram Console.WriteLine(@"5. Generate 100000 samples of the Laplace(0, 4) distribution and display histogram"); data = new double[100000]; laplace.Scale = 4; for (var i = 0; i < data.Length; i++) { data[i] = laplace.Sample(); } ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 6. Generate 100000 samples of the Laplace(-10, 4) distribution and display histogram Console.WriteLine(@"6. Generate 100000 samples of the Laplace(-10 4) distribution and display histogram"); laplace.Location = -10; for (var i = 0; i < data.Length; i++) { data[i] = laplace.Sample(); } ConsoleHelper.DisplayHistogram(data); }
public void SetLocationFailsWithNegativeLocation() { var n = new Laplace(); Assert.Throws<ArgumentOutOfRangeException>(() => n.Location = Double.NaN); }