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stata课堂命令讲解(4)

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接下来

说明非线性判别

. discrimlda price mpg weight length,group(clus5)

Linear discriminant analysis

Resubstitution classification summary

+---------+ | Key | |---------| | Number | | Percent | +---------+

| Classified True clus5 | 1 2 3 | Total -------------+------------------------+-------

1 | 59 0 0 | 59 | 100.00 0.00 0.00 | 100.00 | | 2 | 0 10 0 | 10 | 0.00 100.00 0.00 | 100.00 | | 3 | 0 0 5 | 5 | 0.00 0.00 100.00 | 100.00 -------------+------------------------+-------

Total | 59 10 5 | 74 | 79.73 13.51 6.76 | 100.00

| | Priors | 0.3333 0.3333 0.3333 | 三类有两个判别函数 前文皆在此成立 . estat loadings

Standardized canonical discriminant function coefficients

| function1 function2 -------------+---------------------- price | .9994096 .0619517 mpg | .1147418 .3214297 weight | .7125425 -2.05314 length | -.6690039 2.838476

多元方程分析 . estat loadings

Standardized canonical discriminant function coefficients

| function1 function2 -------------+---------------------- price | .9994096 .0619517 mpg | .1147418 .3214297 weight | .7125425 -2.05314 length | -.6690039 2.838476

. estatgrsum

Estimation sample discrimlda Summarized by clus5

| clus5 Mean | 1 2 3 | Total -------------+---------------------------------+----------

price | 4846.746 9981.5 14091.2 | 6165.257 mpg | 22.49153 17.4 15 | 21.2973 weight | 2824.746 3662 4032 | 3019.459 length | 183.4576 205.2 206.2 | 187.9324 -------------+---------------------------------+----------

N | 59 10 5 | 74

. estatmanova

Number of obs = 74

W = Wilks' lambda L = Lawley-Hotelling trace

P = Pillai's trace R = Roy's largest root

Source | Statisticdf F(df1, df2) = F Prob>F -----------+--------------------------------------------------

clus5 | W 0.1043 2 8.0 136.0 35.63 0.0000 e

| P 0.9304 8.0 138.0 15.00 0.0000 a

| L 8.2507 8.0 134.0 69.10 0.0000 a

| R 8.2102 4.0 69.0 141.63 0.0000 u

|--------------------------------------------------

Residual | 71

-----------+-------------------------------------------------- Total | 73

--------------------------------------------------------------

e = exact, a = approximate, u = upper bound on F .

两次判别qta提高判别率

. discrimqda price mpg weight length, group(foreign)

Quadratic discriminant analysis

Resubstitution classification summary

+---------+ | Key | |---------| | Number | | Percent | +---------+

| Classified True foreign | Domestic Foreign | Total -------------+--------------------+---------

Domestic | 45 7 | 52

| 86.54(提高啦!!!!) | | Foreign | 0 22 | 22 | 0.00 100.00 | 100.00 -------------+--------------------+---------

Total | 45 29 | 74 | 60.81 39.19 | 100.00 | | Priors | 0.5000 0.5000 | 原来的——判别之后的类别及概率 .. estat list

+------------------------------------------------+

| | Classification | Probabilities |

| | | | Obs.| True Class. | Domestic Foreign | |-----+----------------------+-------------------|

| 1 | Domestic Domestic | 1.0000 0.0000 | | 2 | Domestic Domestic | 1.0000 0.0000 | | 3 | Domestic Domestic | 0.9935 0.0065 | | 4 | Domestic Domestic | 1.0000 0.0000 |

13.46 | | 100.00 | 5 | Domestic Domestic | 1.0000 0.0000 | |-----+----------------------+-------------------|

| 6 | Domestic Domestic | 1.0000 0.0000 | | 7 | Domestic Foreign * | 0.2235 0.7765 | | 8 | Domestic Domestic | 1.0000 0.0000 | | 9 | Domestic Domestic | 1.0000 0.0000 | | 10 | Domestic Domestic | 1.0000 0.0000 | |-----+----------------------+-------------------|

| 11 | Domestic Domestic | 1.0000 0.0000 | | 12 | Domestic Domestic | 0.8931 0.1069 | | 13 | Domestic Domestic | 1.0000 0.0000 | | 14 | Domestic Foreign * | 0.2789 0.7211 | | 15 | Domestic Domestic | 1.0000 0.0000 |

总体错判率 . estaterrorrate

Error rate estimated by error count

| foreign

| Domestic Foreign | Total

-------------+----------------------+----------

Error rate | .1346154 (降低了!!!) 0 | .0673077 -------------+----------------------+----------

Priors | .5 .5 |【实际上不一样】 . sum foreign

Variable | Obs Mean Std. Dev. Min -------------+--------------------------------------------------------

foreign | 74 .29729730.3 .4601885 0 改变线性概率再检验

. discrimlda price mpg weight length, group(foreign) priors(0.7,0.3)

Linear discriminant analysis

Resubstitution classification summary

+---------+ | Key | |---------| | Number | | Percent | +---------+

| Classified True foreign | Domestic Foreign | Total

Max 1 -------------+--------------------+---------

Domestic | 44 8 | 52 | 84.62 15.38 | 100.00 | | Foreign | 1 21 | 22 | 4.55 95.45 | 100.00 -------------+--------------------+---------

Total | 45 29 | 74 | 60.81 39.19 | 100.00 | | Priors | 0.7000 0.3000 |

主成份分析

对数据进行降维处理PCA选几个变量出来几个主成份 . pca price mpg weight length turn

Principal components/correlation Number of obs = 74

Number of comp. = 5

Trace = 5

Rotation: (unrotated = principal) Rho = 1.0000

--------------------------------------------------------------------------

Component | Eigenvalue Difference Proportion Cumulative

-------------+------------------------------------------------------------

Comp1 | 3.77621 3.01112 0.7552 0.7552

Comp2 | .76509 .488796 0.1530【两个占总体的90%以上,故选这两个】 0.9083

Comp3 | .276294 .139261 0.0553 0.9635

Comp4 | .137033 .0916582 0.0274 0.9909

Comp5 | .0453749 . 0.0091 1.0000 --------------------------------------------------------------------------

Principal components (eigenvectors)

------------------------------------------------------------------------------

Variable | Comp1 Comp2 Comp3 Comp4 Comp5 | Unexplained

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