八．附录
附录一 clear
x=[18083.89 18367.59 18665.69 18972.82 18948.96 20301.40 20364.60 20747.80 20812.87];
y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; plot(x,y,'r*')
xlabel('国内原油年产量（万吨）'); ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[806.69 633.72 382.92 373.34 518.40 304.22 252.20 243.00 162.00]; y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; plot(x,y,'r*')
xlabel('年原油出口量（万吨）');
ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[53.39 64.29 71.12 96.99 61.76 77.01 94.89 94.12 98.00]; y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; plot(x,y,'r*')
xlabel('国际原油年平均价格（美元/桶）'); ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[12708.32 14518.03 16317.55 17889.30 20378.93 23931.14 25254.92 27102.00 28195.00];
y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35];
20
plot(x,y,'r*')
xlabel('年原油进口量（万吨）');
ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[29985.52 32251.90 34600.31 36488.78 38809.50 43868.33 45367.32 47606.80 48845.87];
y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; plot(x,y,'r*')
xlabel('国内原油年消费量（万吨）'); ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[10493.0 11759.5 13785.8 15780.8 17174.7 19109.4 21809.8 24564.7 26955.1]; y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; z=corrcoef(x,y); plot(x,y,'r*')
xlabel('人均可支配收入（元）');
ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y) clear
x=[235997.00 258676.00 280508.00 291448.00 306647.00 324939.00 348002.00 361732.01 375000.00];
y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; plot(x,y,'r*')
xlabel('全国能源消费总量（万吨标准煤）'); ylabel('国内年平均成品油价格（美元/桶）') z=corrcoef(x,y)
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附录二
clear
x1=[53.39 64.29 71.12 96.99 61.76 77.01 94.89 94.12 98.00]; x2=[18083.89 18367.59 18665.69 18972.82 18948.96 20301.40 20364.60 20747.80 20812.87];
x3=[806.69 633.72 382.92 373.34 518.40 304.22 252.20 243.00 162.00]; x4=[12708.32 14518.03 16317.55 17889.30 20378.93 23931.14 25254.92 27102.00 28195.00];
x5=[29985.52 32251.90 34600.31 36488.78 38809.50 43868.33 45367.32 47606.80 48845.87];
x6=[235997.00 258676.00 280508.00 291448.00 306647.00 324939.00 348002.00 361732.01 375000.00];
x7=[10493.0 11759.5 13785.8 15780.8 17174.7 19109.4 21809.8 24564.7 26955.1];
y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; x=[ones(length(y),1),x1',x2',x3',x4',x5',x6',x7']; Y=y';
[b,bint,r,rint,stats]=regress(Y,x); b,bint,stats b =
-4.2351 1.0593 -0.0366 0.0301 -0.0381 0.0387 -0.0001 -0.0004
stats = 0.9994 249.0376 0.0488 1.4708 附录三
clear
x=[2005 2006 2007 2008 2009 2010 2011 2012 2013];
y1=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35];
y2= [56.1877 68.1287 76.2322 103.4151 64.2150 82.2577 101.5074 100.2089 103.5251];
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plot(x,y1,x,y2,'r:'); legend('实际值','计算值') 附录四
clear syms a b; c=[a,b]';
A=[42.8,50.8,59.6,75.5,97.7,117.5,140.0,161.5,239.3]; B=cumsum(A); %原始数据累加 n=length(A); for i=1:(n-1)
C(i)=(B(i)+B(i+1))/2; %生成累加矩阵 End
% 计算待定参数的值 D=A;D(1)=[]; D=D';
E=[-C;ones(1,n-1)]; c=inv(E*E')*E*D; c=c';
a=c(1);b=c(2); % 预测后续数据 F=[]; F(1)=A(1); for i=2:(n+9)
F(i)=(A(1)-b/a)/exp(a*(i-1))+b/a; end
G=[];G(1)=A(1); for i=2:(n+9)
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G(i)=F(i)-F(i-1); %得到预测出来的数据 end
t1=2006:2014; t2=2006:2023;
G %输出预测值 G =
1.0e+03 *
Columns 1 through 9
0.0428 0.0467 0.0583 0.0728 0.0908 0.1133 0.1413
0.1764 0.2200 Columns 10 through 18
0.2745 0.3426 0.4274 0.5333 0.6654 0.8302 1.0359
1.2924 1.6126 plot(t1,A,'o',t2,G) %原始数据与预测数据比较 xlabel('年份');
ylabel('西安市私家车数量（万辆）') 附录五 lear
x1=[53.39 64.29 71.12 96.99 61.76 77.01 94.89 94.12 98.00];
x3=[806.69 633.72 382.92 373.34 518.40 304.22 252.20 243.00 162.00]; y=[58.4 70.12 77.79 104.82 65.22 82.7 100.79 100.66 102.35]; x=[ones(length(y),1),x1',x3']; Y=y';
[b,bint,r,rint,stats]=regress(Y,x); b,bint,stats
b = -2.4415 1.0794 0.0046
stats = 0.9963 804.6822 0.0000 1.5881 rcoplot(r,rint) %残差图
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