求利用ＳＡＳ进行蒙特卡罗模拟的资料

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如果有这方面的资料，我将重金感谢，一定是程序介绍的．

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关键词：蒙特卡罗模拟 蒙特卡罗 蒙特卡 资料 模拟 蒙特卡罗 ＳＡＳ

MC方法应用很多，你要哪方面的？

sampling技术，MCMC,EM,还是其它？

我都感兴趣,但最好要结合SAS编程来实现,不然只有理论而不能应用就不能体现价值了,如果你有理论方面的也可以吧,谢谢,焦急等待回复.

用sas编程做算法的很少，一般都用c，fortran或者splus/R进行编程验证。

如果你有这方面的资料，可否发送给我harlon1976＠sohu.com，谢谢！

我也感兴趣。yinming65@yahoo.com

/* Monte Carlo Simulation */

data exchange ;

input yr rate_jp rate_wg imn_jp imn_wg emp_us emp_jp emp_wg

prod_us / prod_jp prod_wg cpi_us cpi_jp cpi_wg;

im_jp = imn_jp/cpi_us;

im_wg = imn_wg/cpi_us;

ius = 100*(cpi_us-(lag(cpi_us)))/(lag(cpi_us));

ijp = 100*(cpi_jp-(lag(cpi_jp)))/(lag(cpi_jp));

iwg = 100*(cpi_wg-(lag(cpi_wg)))/(lag(cpi_wg));

di_jp = ius - ijp;

di_wg = ius - iwg;

title 'EXCHANGE Data';

cards;

1974 . . . . . . . .

. . .493 .590 .672

1975 295.78 2.4613 11425 5410 93.0 99.8 103.3 93.5

84.0 89.3 .538 .660 .712

1976 296.45 2.5184 15504 5592 96.4 100.8 100.8 97.1

95.6 94.9 .569 .721 .742

1977 268.62 2.3236 18550 7238 100.0 100.0 100.0 100.0

100.0 100.0 .606 .780 .769

1978 210.38 2.0096 24458 9962 104.2 98.9 99.4 100.9

106.8 103.8 .652 .813 .790

1979 219.02 1.8342 26248 10955 107.1 98.1 99.8 101.5

117.4 108.9 .726 .843 .823

1980 226.63 1.8175 30714 11693 103.3 101.3 100.4 101.7

125.4 109.8 .824 .909 .868

1981 220.63 2.2631 37612 11379 102.8 102.2 97.9 104.6

126.3 112.8 .909 .954 .922

1982 249.06 2.4280 37744 11975 95.8 101.4 95.0 107.1

146.8 113.3 .965 .980 .970

1983 237.55 2.5539 41183 12695 94.4 103.4 91.1 111.6

152.8 116.8 .996 .999 1.003

1984 237.45 2.8454 57135 16996 99.0 105.8 90.4 118.5

152.2 124.7 1.039 1.021 1.027

1985 238.47 2.9419 68783 20239 98.1 107.6 91.3 124.2

161.1 128.5 1.076 1.042 1.048

1986 168.35 2.1704 81911 25124 96.8 107.3 92.7 128.8

163.8 130.7 1.096 1.049 1.047

1987 144.60 1.7981 84575 27069 97.1 106.1 92.8 132.0

176.5 129.9 1.136 1.050 1.049

1988 128.17 1.7569 89802 26503 99.6 108.8 92.7 136.2

190.0 135.9 1.183 1.057 1.063

;

/* data for simulation */

data whatif;

input yr rate_jp rate_wg imn_jp imn_wg emp_us emp_jp emp_wg

prod_us / prod_jp prod_wg cpi_us cpi_jp cpi_wg;

label cpi_us = 'US CPI 1982-1984 = 100'

cpi_jp = 'JP CPI 1982-1984 = 100'

cpi_wg = 'WG CPI 1982-1984 = 100';

im_jp = imn_jp/cpi_us;

im_wg = imn_wg/cpi_us;

ius = 100*(cpi_us-(lag(cpi_us)))/(lag(cpi_us));

ijp = 100*(cpi_jp-(lag(cpi_jp)))/(lag(cpi_jp));

iwg = 100*(cpi_wg-(lag(cpi_wg)))/(lag(cpi_wg));

di_jp = ius - ijp;

di_wg = ius - iwg;

cards;

1980 226.63 1.8175 30714 11693 103.3 101.3 100.4 101.7

125.4 109.8 .824 .909 .868

1981 220.63 2.2631 35000 11000 102.8 102.2 97.9 104.6

126.3 112.8 .909 .954 .922

1982 249.06 2.4280 40000 12000 95.8 101.4 95.0 107.1

146.8 113.3 .965 .980 .970

1983 237.55 2.5539 45000 13100 94.4 103.4 91.1 111.6

152.8 116.8 .996 .999 1.003

1984 237.45 2.8454 50000 14300 99.0 105.8 90.4 118.5

152.2 124.7 1.039 1.021 1.027

1985 238.47 2.9419 55000 15600 98.1 107.6 91.3 124.2

161.1 128.5 1.076 1.042 1.048

1986 . . 60000 17000 96.8 107.3 92.7 128.8

163.8 130.7 1.096 1.049 1.047

1987 . . 65000 18500 97.1 106.1 92.8 132.0

176.5 129.9 1.136 1.050 1.049

1988 . . 70000 20000 99.6 108.8 92.7 136.2

190.0 135.9 1.183 1.057 1.063

;

proc model data=exchange outmodel=xch_out;

parms a1 a2 b1 b2 c1 c2;

label rate_jp = 'Exchange Rate of Yen/$'

rate_wg = 'Exchange Rate of Gm/$'

im_jp = 'Imports to US from Japan in 1984 $'

im_wg = 'Imports to US from WG in 1984 $'

di_jp = 'Difference in Inflation Rates US-JP'

di_wg = 'Difference in Inflation Rates US-WG';

rate_jp = a1 + b1*im_jp + c1*di_jp;

rate_wg = a2 + b2*im_wg + c2*di_wg;

endo im_jp im_wg;

exo di_jp di_wg;

fit rate_jp rate_wg / sur outest=xch_est outcov outs=s;

solve rate_jp rate_wg / data=whatif estdata=xch_est sdata=s

random=100 seed=123 out=monte forecast;

id yr;

range yr=1986;

run;

proc sort data=monte;

by yr;

run;

proc univariate data=monte noprint;

by yr;

var rate_jp rate_wg;

output out=bounds mean=mean p5=p5 p95=p95;

run;

title "Monte Carlo Generated Confidence Intervals on a Forecast";

proc gplot data=bounds;

plot mean*yr p5*yr p95*yr /overlay;

symbol1 i=join value=triangle;

symbol2 i=join value=square l=4;

symbol3 i=join value=square l=4;

run;

我有蒙特卡罗理论与程序方面的书籍

需要者与我联系zlb1216@yahoo.com.cn

我也感兴趣，楼上的有电子版吗，yudaojun@163.com

需要的请到  这里  下载

http://dyn.www.fs2you.com/zh-cn/manage/

[此贴子已经被作者于2007-12-27 22:58:38编辑过]