exponentregress.cs

指数回归方程 ExponentRegress.cs 方程模型为 public override double[] buildFormula() 得到系数数组

using System;

namespace InfieldForecast.ForecastModels
{
	/// <summary>
	/// 指数回归方程
	/// </summary>
	/// 

	public class ExponentRegress : RegressFormulaStrategy
	{
		private LinearRegress linearRegress;
		private double[] lnYArray;
		/// <summary>
		/// 构造函数
		/// </summary>
		/// <param name="xArray">时间序列数组</param>
		/// <param name="yArray">观察值数组</param>
		public ExponentRegress(double[] xArray,double[] yArray)
		{
			//
			// TODO: 在此处添加构造函数逻辑
			//
			this.xArray=xArray;
			this.yArray=yArray;
			init();
		}
		private void init()
		{
			this.lnYArray=new double[yArray.Length];
			for(int i=0;i<yArray.Length;i++)
			{
				lnYArray[i]=Math.Log(yArray[i],Math.E);
			}
			 this.linearRegress=new LinearRegress(xArray,lnYArray);
		}
		public override double[] buildFormula()
		{
			double[] coefficient=this.linearRegress.buildFormula();
			coefficient[0]=Math.Pow(Math.E,coefficient[0]);
			coefficient[1]=Math.Pow(Math.E,coefficient[1]);
			reverseArray(coefficient);
			return coefficient;
		}
		private void reverseArray(double[] dataArray)
		{
			double temp=dataArray[0];
			dataArray[0]=dataArray[1];
			dataArray[1]=temp;
		}
		public override double computeR2()
		{
			return this.linearRegress.computeR2();
		}
		public override double computeR()
		{
			return Math.Sqrt(computeR2());
		}
		
		public override double forecast(double x)
		{
			double[] coefficientArray=getCoefficientArray();
			return coefficientArray[1]*Math.Pow(coefficientArray[0],x);
		}
		
		
	}
}