许久没有管自己的博客了，问我要源码的亲们，现在可以看了，希望可以帮到你们。
代码如下：
import java.sql.ResultSet; import java.sql.SQLException; import java.util.ArrayList; import java.util.Comparator; import java.util.HashMap; import java.util.Iterator; import java.util.List; import java.util.Map; import java.util.TreeMap; import Jama.Matrix; import Util.DBConnection; //因子分析 public class FactorAnalyse { // 从数据库中获取数据 public double[][] getHseData(){ List<Double> list = new ArrayList<Double>(); double[][] result = new double[24][26]; double[] temp = new double[24*26]; String sql = "select score from HseScore"; ResultSet rs = DBConnection.executeQuery(sql); try{ while(rs.next()){ list.add(rs.getDouble(1)); } }catch(SQLException e){ e.printStackTrace(); } for(int i=0;i<list.size();i++){ temp[i] = list.get(i); } for (int i = 0; i < 24; i++) { for (int j = 0; j < 26; j++) { result[i][j] = temp[26*i+j]; } } Matrix m = new Matrix(result); m.print(3, 2); return result; } // 计算均值 public double[] getAverage(double[][] array) { int h = array.length; // 行号--h int l = array[0].length;// 列号--l double[] average = new double[l];// 每个变量的均值 for (int i = 0; i < l; i++) { double temp = 0.0; for (int j = 0; j < h; j++) { temp += array[j][i]; } average[i] = temp / h; // System.out.printf("average[%d] = %.5f\n", i, average[i]); } return average; } // 计算方差 public double[] getVariance(double[][] array) { int h = array.length; // 行号--h int l = array[0].length;// 列号--l double[] average = getAverage(array); double[] var = new double[l]; for (int i = 0; i < l; i++) { double temp = 0.0; for (int j = 0; j < h; j++) { temp += Math.pow((array[j][i] - average[i]), 2); } var[i] = temp / (h - 1); // System.out.printf("var[%d] = %.5f\n", i, var[i]); } return var; } // 计算标准差 public double[] getStandardDevition(double[] var) { double[] sd = new double[var.length]; for (int i = 0; i < var.length; i++) { sd[i] = Math.sqrt(var[i]); // System.out.printf("sd[%d] = %.5f\n", i, sd[i]); } return sd; } // 标准化数据 public double[][] getStandard(double[][] array, double[] sd) { int h = array.length; // 行号--h int l = array[0].length;// 列号--l double[][] result = new double[h][l];// 标准化 double[] average = getAverage(array); for (int i = 0; i < h; i++) { for (int j = 0; j < l; j++) { result[i][j] = (array[i][j] - average[j]) / sd[j]; } } Matrix m = new Matrix(result); m.print(5, 3); return result; } // 计算协方差矩阵--方阵 public double[][] getCovMatrix(double[][] array) { int h = array.length; int l = array[0].length; double[][] temp = new double[h][l];// 保存计算协方差的中间矩阵 double[][] result = new double[l][l]; double[] average = getAverage(array); // 标准化后的矩阵求均值 for (int i = 0; i < h; i++) { for (int j = 0; j < l; j++) { temp[i][j] = array[i][j] - average[j]; } } for (int i = 0; i < l; i++) { for (int j = 0; j < l; j++) { double t = 0; for (int k = 0; k < h; k++) { t += temp[k][i] * temp[k][j]; } result[i][j] = t / (h - 1); } } Matrix m = new Matrix(result); m.print(5, 3); return result; } // 计算相关矩阵---方阵 public double[][] getCorrelationMatrix(double[][] cov, double[] sd) { int l = cov.length; double[][] result = new double[l][l]; for (int i = 0; i < l; i++) { for (int j = 0; j < l; j++) { result[i][j] = cov[i][j] / (sd[i] * sd[j]); } } Matrix m = new Matrix(result); m.print(5, 3); return result; } // 求矩阵特征值 public double[][] getEigenvalue(double[][] array) { int h = array.length;// 行号等于列号 double[][] result = new double[h][h]; Matrix m = new Matrix(array); Matrix m1 = m.eig().getD(); // 由特征值组成的对角矩阵 System.out.println("由特征值组成的对角矩阵："); m1.print(5, 3); result = m1.getArray(); return result; } // 求矩阵的特征向量 public double[][] getEigenvector(double[][] array) { int h = array.length;// 行号等于列号 double[][] result = new double[h][h]; Matrix m = new Matrix(array); Matrix m1 = m.eig().getV(); // 该矩阵的每一列对应的是一个单位正交特征向量 System.out.println("\n特征向量矩阵："); m1.print(5, 3); result = m1.getArray(); return result; } // 特征值从大到小排序并保存成键值对形式 public TreeMap<Integer, Double> getMap(double[][] array) { int h = array.length; Map<Integer, Double> map = new HashMap<Integer, Double>(); ValueComparator bvc = new ValueComparator(map); TreeMap<Integer, Double> sorted_map = new TreeMap<Integer, Double>(bvc); double[] temp = new double[h]; // 存储特征值 for (int i = 0; i < h; i++) { for (int j = 0; j < h; j++) { if (i == j) temp[i] = array[i][j]; } } for (int i = 0; i < temp.length; i++) { map.put(i, temp[i]); } System.out.println("\n排序前键值对：\n" + map); sorted_map.putAll(map); System.out.println("\n排序后的键值对：\n" + sorted_map); return sorted_map; } // 计算方差贡献率 public double[] getContibutionRatio(TreeMap<Integer, Double> tm) { int h = tm.size(); double[] percent = new double[h]; Iterator titer = tm.entrySet().iterator(); int count = 0; while (titer.hasNext()) { Map.Entry ent = (Map.Entry) titer.next(); int keyt = (Integer) ent.getKey(); double valuet = (Double) ent.getValue(); percent[count] = valuet / h; System.out.printf("\n键%d 对应的特征值 %.3f所占的比例为 %.3f \n",keyt,valuet,percent[count]); count++; } return percent; } // 计算方差累积贡献率 public double[] getCumuContributionRatio(double[] array) { double[] result = new double[array.length]; double temp = 0.0; for (int i = 0; i < array.length; i++) { temp += array[i]; result[i] = temp; System.out.printf("\n累积贡献率：%.3f \n", result[i]); } return result; } // 确定公共因子的个数 public int getNum(double[] array) { int number = 1;// 公因子个数 double t = 0.0; for (int i = 0; i < array.length; i++) { t = array[i]; if (t < 0.75) number++; } System.out.println("\n公共因子个数：" + number); return number; } // 获取特征值对应的特征向量 public double[][] getVVector(TreeMap<Integer, Double> tm, double[][] array) { int h = array.length; double[][] result = new double[h][h]; int[] temp = new int[h]; Iterator titer = tm.entrySet().iterator(); int count = 0; while (titer.hasNext()) { Map.Entry ent = (Map.Entry) titer.next(); int keyt = (Integer) ent.getKey(); temp[count] = keyt; // System.out.println("temp["+count+"] = "+temp[count]); count++; } for (int i = 0; i < h; i++) { for (int j = 0; j < h; j++) { result[i][j] = array[i][temp[j]]; } } System.out.println("特征值对应的特征向量组成的矩阵："); Matrix m = new Matrix(result); m.print(5, 3); return result; } // 获取因子载荷矩阵 public double[][] getMatrixA(TreeMap<Integer, Double> tm, double[][] array, int num) { int h = array.length; double[][] A = new double[h][num]; double[] temp = new double[h]; Iterator titer = tm.entrySet().iterator(); int count = 0; while (titer.hasNext()) { Map.Entry ent = (Map.Entry) titer.next(); double valuet = (Double) ent.getValue(); temp[count] = Math.sqrt(valuet); // System.out.printf("特征值开平方根：%.5f\n", temp[count]); count++; } System.out.println("因子载荷矩阵 A = "); for (int i = 0; i < h; i++) { for (int j = 0; j < num; j++) { A[i][j] = temp[j] * array[i][j]; } } Matrix m = new Matrix(A); m.print(5, 3); return A; } // 获取特殊因子矩阵 public double[][] getMatrixD(TreeMap<Integer, Double> tm, double[][] array, int num) { int h = array.length; double[][] B = new double[h][h - num]; double[][] C = new double[h][h]; double[][] D = new double[h][h]; double[] temp = new double[h]; Iterator titer = tm.entrySet().iterator(); int count = 0; while (titer.hasNext()) { Map.Entry ent = (Map.Entry) titer.next(); double valuet = (Double) ent.getValue(); temp[count] = Math.sqrt(valuet); count++; } for (int i = 0; i < h; i++) { for (int j = num; j < h; j++) { B[i][j - num] = temp[j] * array[i][j]; } } Matrix m = new Matrix(B); Matrix m1 = m.times(m.transpose()); C = m1.getArray(); for (int i = 0; i < h; i++) { for (int j = 0; j < h; j++) { if (i == j) D[i][j] = C[i][j]; } } System.out.println("特殊因子矩阵 D = "); Matrix m2 = new Matrix(D); m2.print(5, 3); return D; } // 进行因子旋转--方差最大正交旋转 public double[][] getVarimax(double[][] array, int num) { int h = array.length; int l = array[0].length; double[] hi = new double[h]; // 变量共同度 double[][] standardA = new double[h][l];//标准化处理因子载荷阵 double[][] result = new double[h][l];// 旋转后的因子载荷矩阵 double[] u = new double[h]; double[] v = new double[h]; double A = 0.0; double B = 0.0; double C = 0.0; double D = 0.0; double E = 0.0; //标准化处理A for (int i = 0; i < h; i++) { double temp = 0.0; for (int j = 0; j < l; j++) { temp += Math.pow(array[i][j], 2); } hi[i] = temp; //System.out.printf("变量共同度：%.5f\n", hi[i]); } for(int i = 0; i < h; i++){ for(int j = 0; j < l; j++){ standardA[i][j] = Math.pow(array[i][j],2) / hi[i]; } } double[][] P = new double[l][l]; // 构造正交矩阵 Matrix m = new Matrix(standardA); for (int k = 0; k < num-1; k++) { for (int p = k+1; p < num; p++) { for (int i = 0; i < h; i++) { u[i] = (Math.pow(array[i][k], 2) - Math.pow(array[i][p], 2)) / hi[i]; } for (int i = 0; i < h; i++) { v[i] = (2 * array[i][k] * array[i][p]) / hi[i]; } for (int i = 0; i < h; i++) { A += u[i]; B += v[i]; C += (u[i] * u[i]) - (v[i] * v[i]); D += 2 * u[i] * v[i]; } E = (Math.atan((D - (2 * A * B) / h) / (C - (A * A - B * B) / h))) / 4.0; //System.out.printf("\n旋转角度 E = %.5f\n", E); for (int i = 0; i < l; i++) { for (int j = 0; j < l; j++) { if (i == j) P[i][j] = 1; else P[i][j] = 0; } } double[][] T = P; T[k][k] = Math.cos(E); T[k][p] = -Math.sin(E); T[p][k] = Math.sin(E); T[p][p] = Math.cos(E); Matrix m1 = new Matrix(T);//正交矩阵 m = m.times(m1); } } m.print(5, 3); result = m.getArray(); return result; } // 计算旋转后的方差贡献率 public double[] getContibutionRatio1(double[][] array) { int h = array.length; int l = array[0].length; double[] percent = new double[h]; double sum = 0.0; for(int i = 0; i < l;i++){ double temp = 0.0; for(int j = 0; j < h;j++){ temp += Math.pow(array[j][i],2); } percent[i] = temp / h; //System.out.printf("\n旋转后的方差贡献率--F["+(i+1)+"]: %.3f\n",percent[i]); sum += percent[i]; } //System.out.printf("\n方差累积贡献率：:%.3f\n",sum); return percent; } // 计算因子载荷的方差 public double getA_Var(double[][] array) { int h = array.length; int l = array[0].length; double[] var = new double[l];// 每一列的方差 double v = 0.0;// 总方差 double[][] B = new double[h][l]; for (int i = 0; i < h; i++) { for (int j = 0; j < l; j++) { B[i][j] = Math.pow(array[i][j],2); } } double[] ad = getAverage(B); for (int i = 0; i < l; i++) { double temp = 0.0; for (int j = 0; j < h; j++) { temp += Math.pow(B[j][i] - ad[i], 2); } var[i] = temp / h; //System.out.printf("每一列的方差：%.5f\n", var[i]); v += var[i]; } System.out.printf("总方差：%.3f\n", v); return v; } // 计算因子得分 public double[][] getScore(double[][] R, double[][] A,double[][] array) { int h = A.length; int l = R[0].length; double[][] F = new double[h][l]; Matrix m = new Matrix(A); Matrix m1 = new Matrix(R); Matrix m2 = (m.transpose()).times(m1.inverse()); Matrix m3 = new Matrix(array); Matrix m4 = (m2).times(m3.transpose()); System.out.println("因子得分："); m4.transpose().print(5, 3); F = m4.transpose().getArray(); return F; } //计算因子综合得分 public double[] getScores(double[][] array,double[] percent){ int h = array.length; int l = array[0].length; double[] result = new double[h]; double temp = 0.0; for(int i = 0; i < l; i++){ temp +=percent[i]; } for(int i = 0; i < h; i++){ double t = 0.0; for(int j = 0; j < l; j++){ t += array[i][j] * percent[j]; } result[i] = t / temp; System.out.printf("综合得分：%.3f\n",result[i]); } return result; } } // map按值进行排序 class ValueComparator implements Comparator<Integer> { Map<Integer, Double> base; public ValueComparator(Map<Integer, Double> base) { this.base = base; } public int compare(Integer a, Integer b) { if (base.get(a) >= base.get(b)) { return -1; } else { return 1; } } }完整代码已贴出，有需要的朋友请查看，转载请注明出处，谢谢！
