📄 statdist.java
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package com.Code;
import com.Code.*;
import java.util.*;
import java.lang.*;
public class StatDist {
public StatDist() {
}
/*
*定义常量E
*/
public static final double E = 2.7182818284590452354;
/*
*定义常量PI
*/
public static final double PI = 3.14159265358979323846;
/*
* Desc: The probability density function
*正态分布某点的概率密度
*输入参数：
* @param double avg 正态分布的数学期望
* @param double stddev 正态分布的标准方差
* @param double point 检测点
*输出参数：
*/
public static double norminc(double point, double avg, double stddev) {
if (stddev == 0) {
return 1;
} else {
double a = (point - avg) / stddev;
a = a * a / 2.0;
return Math.exp(-a) / Math.sqrt(2.0 * PI * stddev);
}
}
/*
*正态分布函数反函数，根据分布概率值获得区间点，本质是解积分方程，
*注：任何一个正态分布函数的反函数等于avg+stddev * stdnorminv(double x),avg为平均值，stddev
*为方差，stdnorminv(double x)为标准正态分布函数的反函数，其对照值写死在本函数中，本函数只精确到小数点后两位，穷举了100个点
*/
public static double norminv(double integral, double avg, double stddev) {
/*
*如果分布值是0.5,那么分布点肯定是avg，本函数只精确到小数点后2位
*/
double POSITIVE_INFINITY = 1.0 / 0.0;
double NEGATIVE_INFINITY = -1.0 / 0.0;
double point;
//根据3倍偏差原则，如果为0，则返回avg-3*stddev,如果为1，则返回avg+3*stddev
if (integral == 0) {
point = avg - 3 * stddev;
//System.out.println("The parameter is unormal ");
} else if (integral == 1) {
point = avg + 3 * stddev;
//System.out.println("The parameter is unormal ");
} else {
double stdpoint = 0;
Double temp = new Double(integral * 100);
int iswith = temp.intValue();
switch (iswith) {
case 1 :
stdpoint = -2.326347000;
break;
case 2 :
stdpoint = -2.053747519;
break;
case 3 :
stdpoint = -1.880792650;
break;
case 4 :
stdpoint = -1.750685567;
break;
case 5 :
stdpoint = -1.644853476;
break;
case 6 :
stdpoint = -1.554773691;
break;
case 7 :
stdpoint = -1.475791283;
break;
case 8 :
stdpoint = -1.405071903;
break;
case 9 :
stdpoint = -1.340755412;
break;
case 10 :
stdpoint = -1.281551939;
break;
case 11 :
stdpoint = -1.226528461;
break;
case 12 :
stdpoint = -1.174987081;
break;
case 13 :
stdpoint = -1.126391354;
break;
case 14 :
stdpoint = -1.080319496;
break;
case 15 :
stdpoint = -1.036433474;
break;
case 16 :
stdpoint = -0.994457898;
break;
case 17 :
stdpoint = -0.954165204;
break;
case 18 :
stdpoint = -0.915364982;
break;
case 19 :
stdpoint = -0.877896141;
break;
case 20 :
stdpoint = -0.841621042;
break;
case 21 :
stdpoint = -0.806421028;
break;
case 22 :
stdpoint = -0.772192978;
break;
case 23 :
stdpoint = -0.738846607;
break;
case 24 :
stdpoint = -0.706302325;
break;
case 25 :
stdpoint = -0.674489526;
break;
case 26 :
stdpoint = -0.643345203;
break;
case 27 :
stdpoint = -0.612812818;
break;
case 28 :
stdpoint = -0.58284137;
break;
case 29 :
stdpoint = -0.553384622;
break;
case 30 :
stdpoint = -0.524400458;
break;
case 31 :
stdpoint = -0.495850336;
break;
case 32 :
stdpoint = -0.467698831;
break;
case 33 :
stdpoint = -0.439913238;
break;
case 34 :
stdpoint = -0.412463237;
break;
case 35 :
stdpoint = -0.385320604;
break;
case 36 :
stdpoint = -0.358458952;
break;
case 37 :
stdpoint = -0.331853516;
break;
case 38 :
stdpoint = -0.305480959;
break;
case 39 :
stdpoint = -0.279319195;
break;
case 40 :
stdpoint = -0.253347241;
break;
case 41 :
stdpoint = -0.227545081;
break;
case 42 :
stdpoint = -0.20189354;
break;
case 43 :
stdpoint = -0.176374174;
break;
case 44 :
stdpoint = -0.150969169;
break;
case 45 :
stdpoint = -0.125661246;
break;
case 46 :
stdpoint = -0.100433574;
break;
case 47 :
stdpoint = -0.075269689;
break;
case 48 :
stdpoint = -0.050153414;
break;
case 49 :
stdpoint = -0.02506879;
break;
case 50 :
stdpoint = 0.00000000;
break;
case 51 :
stdpoint = 0.02506879;
break;
case 52 :
stdpoint = 0.050153414;
break;
case 53 :
stdpoint = 0.075269689;
break;
case 54 :
stdpoint = 0.100433574;
break;
case 55 :
stdpoint = 0.125661246;
break;
case 56 :
stdpoint = 0.150969169;
break;
case 57 :
stdpoint = 0.176374174;
break;
case 58 :
stdpoint = 0.20189354;
break;
case 59 :
stdpoint = 0.227545081;
break;
case 60 :
stdpoint = 0.253347241;
break;
case 61 :
stdpoint = 0.279319195;
break;
case 62 :
stdpoint = 0.305480959;
break;
case 63 :
stdpoint = 0.331853516;
break;
case 64 :
stdpoint = 0.358458952;
break;
case 65 :
stdpoint = 0.385320604;
break;
case 66 :
stdpoint = 0.412463237;
break;
case 67 :
stdpoint = 0.439913238;
break;
case 68 :
stdpoint = 0.467698831;
break;
case 69 :
stdpoint = 0.495850336;
break;
case 70 :
stdpoint = 0.524400458;
break;
case 80 :
stdpoint = 0.841621042;
break;
case 79 :
stdpoint = 0.806421028;
break;
case 78 :
stdpoint = 0.772192978;
break;
case 77 :
stdpoint = 0.738846607;
break;
case 76 :
stdpoint = 0.706302325;
break;
case 75 :
stdpoint = 0.674489526;
break;
case 74 :
stdpoint = 0.643345203;
break;
case 73 :
stdpoint = 0.612812818;
break;
case 72 :
stdpoint = 0.58284137;
break;
case 71 :
stdpoint = 0.553384622;
break;
case 90 :
stdpoint = 1.281551939;
break;
case 89 :
stdpoint = 1.226528461;
break;
case 88 :
stdpoint = 1.174987081;
break;
case 87 :
stdpoint = 1.126391354;
break;
case 86 :
stdpoint = 1.080319496;
break;
case 85 :
stdpoint = 1.036433474;
break;
case 84 :
stdpoint = 0.994457898;
break;
case 83 :
stdpoint = 0.954165204;
break;
case 82 :
stdpoint = 0.915364982;
break;
case 81 :
stdpoint = 0.877896141;
break;
case 99 :
stdpoint = 2.326347000;
break;
case 98 :
stdpoint = 2.053747519;
break;
case 97 :
stdpoint = 1.880792650;
break;
case 96 :
stdpoint = 1.750685567;
break;
case 95 :
stdpoint = 1.644853476;
break;
case 94 :
stdpoint = 1.554773691;
break;
case 93 :
stdpoint = 1.475791283;
break;
case 92 :
stdpoint = 1.405071903;
break;
case 91 :
stdpoint = 1.340755412;
break;
}
point = avg + stddev * stdpoint;
}
return point;
}
public static void main(String[] args)
{
ArrayList seasonSample = new ArrayList();
HashMap temp = new HashMap();
temp.put("PERIOD","2002");
temp.put("SEASON","Y1");
temp.put("VALUE","150");
seasonSample.add(0,temp);
temp = new HashMap();
temp.put("PERIOD","2002");
temp.put("SEASON","Y2");
temp.put("VALUE","140");
seasonSample.add(1,temp);
temp = new HashMap();
temp.put("PERIOD","2003");
temp.put("SEASON","Y1");
temp.put("VALUE","160");
seasonSample.add(2,temp);
temp = new HashMap();
temp.put("PERIOD","2003");
temp.put("SEASON","Y2");
temp.put("VALUE","150");
seasonSample.add(3,temp);
temp = new HashMap();
temp.put("PERIOD","2004");
temp.put("SEASON","Y1");
temp.put("VALUE","170");
seasonSample.add(4,temp);
ArrayList SeasonList = new ArrayList();
temp = new HashMap();
temp.put("SEASON","Y1");
temp.put("SEASON_INDEX","1");
SeasonList.add(0,temp);
temp = new HashMap();
temp.put("SEASON","Y2");
temp.put("SEASON_INDEX","1");
SeasonList.add(1,temp);
double res = TimeSerial.seasonTimeSerialForecast(seasonSample,SeasonList,"2004","Y2");
System.out.println("THe forecast result is .."+res);
double[] test = new double[5];
test[0]=3.0;
test[1]=3.0;
res = Base.min(test);
System.out.println("The res is ---"+res);
}
}
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