[求助]spss岭回归分析结果解读。各位大侠帮忙阿～～

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<P>因变量：gdp</P>
<P>自变量：国有化，市场化，开放程度</P>
<P>根据"制度变量含2002数据"最小二乘法回归，结果在output1.直接给出变量参数</P>
<P>进行岭回归分析,调用宏“Syntax1制度因素岭回归.SPS”在，运行后结果在"output2"
可是output2只给出了（Standardized Coefficients Beta）却没有返回自变量参数，请问怎么计算参数（Unstandardized Coefficients）？</P>
<P>不知别的软件对岭回归结果实现得如何，有没有直接给出的参数阿？</P>
<P>如有高人指点不胜感激。我的Q是76389，先谢谢了！！</P>

[此贴子已经被作者于2005-4-21 10:45:14编辑过]

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关键词：各位大侠 回归分析 SPSS PSS 岭回归 回归分析 不胜感激 因变量 自变量 如何

Multicollinearity (cont)

• Special case: polynomial regression (cont)
• Ridge Regression (8.4)
  • For a given shrinkage parameter, k, how it is done.
  • Why it reduces the impact of multicollinearity on variances of coefficients.
  • Magnitude of the bias.
  • Scaling vs scaling and centering: if center, don't shrink intercept.
  • Selecting shrinkage parameter
    • Graphical device: ridge trace, coefficients vs k
    • C_k measure (related to Mallow's C_p)
    • Leave-one-out cross validation of prediction errors
      • An approximation, PR(Ridge)
    • Generalized cross validation, GCV
    • Examining VIF's as function of k
    • df-trace criterion

  • SAS code for fitting ridge and drawing trace

  • S-Plus code for fitting ridge model, drawing trace, PRESS, C_k

原始数据

. . .gdp . .nsow mrl orl

1978.00 100.00 22.37 . 9.80

1979.00 107.60 21.53 . 11.26

1980.00 116.00 24.03 . 12.26

1981.00 122.00 25.24 59.20 15.12

1982.00 133.30 26.64 63.00 14.57

1983.00 148.20 26.64 63.90 14.49

1984.00 170.90 30.91 62.90 16.75

1985.00 193.50 35.14 63.90 23.05

1986.00 209.50 37.73 64.30 25.29

1987.00 234.10 40.28 63.90 25.78

1988.00 260.50 43.21 69.70 25.60

1989.00 271.50 43.93 74.40 24.58

1990.00 283.00 45.39 71.70 29.98

1991.00 308.80 43.84 69.70 33.43

1992.00 352.20 48.48 68.30 34.24

1993.00 398.40 53.05 72.80 32.54

1994.00 448.70 61.96 74.60 43.59

1995.00 489.10 66.03 76.50 40.19

1996.00 536.80 71.52 77.80 35.55

1997.00 582.90 74.48 78.30 36.22

1998.00 628.40 78.43 76.50 34.28

1999.00 673.50 79.69 74.50 36.43

2000.00 729.60 77.97 73.30 43.93

2001.00 780.60 81.95 75.78 44.07

2002.00 848.90 84.41 75.92 49.62

		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model
	B	Std. Error	Beta
1
(Constant)	320.529	174.228		1.840	.082
NSOW	12.425	1.184	1.108	10.496	.000
MRL	-9.188	3.059	-.238	-3.004	.008
ORL	2.032	1.901	.092	1.069	.299

这是最小二乘的结果，它把参数都给出来了。

可是岭回归给出的结果只有岭迹图，和下表

R-SQUARE AND BETA COEFFICIENTS FOR ESTIMATED VALUES OF K

K RSQ NSOW MRL ORL

______ ______ ________ ________ ________

.00000 .97570 1.108390 -.238223 .092451

.05000 .96431 .809517 -.069899 .213568

.10000 .95084 .672341 .012790 .254793

.15000 .93994 .591961 .061931 .271769

.20000 .93098 .538219 .094082 .278904

.25000 .92328 .499162 .116356 .281345

.30000 .91639 .469095 .132365 .281308

.35000 .91003 .444956 .144154 .279874

.40000 .90403 .424948 .152973 .277619

.45000 .89826 .407947 .159628 .274871

.50000 .89264 .393212 .164665 .271829

.55000 .88713 .380234 .168466 .268613

.60000 .88169 .368651 .171306 .265304

.65000 .87628 .358199 .173388 .261953

.70000 .87091 .348680 .174866 .258596

.75000 .86556 .339943 .175855 .255256

.80000 .86022 .331869 .176449 .251949

.85000 .85489 .324365 .176718 .248687

.90000 .84957 .317355 .176720 .245476

.95000 .84426 .310779 .176502 .242323

1.0000 .83895 .304585 .176101 .239229

_

请问如何求自变量参数？

嗨 把标准化后的自变量和因变量还原为 为标准化的不就行了

从0到1之间每取一个值都有一个参数 一般选择稳定的那个区间的参数，没有精确的参数的

回归——》最优尺度——》规则化里面有岭回归的，不用那么麻烦了spss18里面已经比较完善了

能否告知具体操作过程？
5# huzi_06

同求，同求

我也遇到了相似的问题哦

来学习一下~