for nonsymmetric matrix,

.matrix eigenvalues r c=A

where r and c are both row vectors.r contains the real part of the eigenvalues, and c contains the imaginary part.

for symmetric matrix

.matrix symeigen X v=A

where X is n*n matrix,which contains the eigenvectors.

v contains the contains the corresponding eigenvalues.

best

[此贴子已经被作者于2007-5-4 18:31:21编辑过]

谢谢布丁兄。

借此再请教一个问题。因为我不知STATA如何进行JOHANSEN的协整检验，所以我就尝试用"APPLIED TIME SERIES ANALYSIS"一书上讲的Johansen方法，逐步计算trace和max统计量，以之来进行检验。具体步骤如下。

1)先水平VAR，估计Lag value is 2;

2)估计Trace and Max 统计量

方法一：估计 X(t)=A0+A1*X(t-1)+A2*X(t-1)

计算矩阵Pi=-(E-A1-A2)，在计算Pi的特征值，从而得到Trace and Max ；

方法二：估计D.X(t)=A0+A1*X(t-1)+A2*D.X(t-1)(D. denotes difference)

在计算A1的特征值，从而得到Trace and Max.

我的问题是：1.我按照上述两种方法得到的特征均是负数，而用EVIEWS得到的特征均是正数，请问我的方法上有什么问题？

2. STATA如何进行Johansen 的协整检验？

谢谢。我的数据如下。

ln_Exchange_Rate ln_PPI_America ln_PPI_China
6.720678 4.635699 4.611252
6.720799 4.61611 4.614526
6.720992 4.61512 4.612543
6.720775 4.609162 4.608365
6.72051 4.607168 4.607168
6.720317 4.60517 4.601463
6.720232 4.602166 4.603569
6.720039 4.60617 4.59744
6.719641 4.607168 4.597843
6.719448 4.610157 4.597642
6.719025 4.607168 4.601664
6.718989 4.60617 4.599353
6.71888 4.601162 4.589345
6.718893 4.600158 4.577696
6.718904 4.599152 4.569025
6.718784 4.601162 4.566326
6.718953 4.599152 4.549446
6.718989 4.598145 4.55008
6.719001 4.601162 4.548494
6.719013 4.598145 4.543295
6.718771 4.598145 4.542656
6.718723 4.602166 4.540952
6.718796 4.601162 4.541485
6.718856 4.60517 4.541591
6.718748 4.608166 4.551453
6.71888 4.60417 4.550609
6.719013 4.607168 4.55724
6.718941 4.611152 4.567157
6.718844 4.613138 4.571924
6.718844 4.61413 4.574608
6.718687 4.61611 4.585172
6.718663 4.622027 4.590868
6.718711 4.629863 4.595221
6.718723 4.628887 4.610556
6.71888 4.632785 4.611749
6.718929 4.634729 4.614923
6.718784 4.634729 4.62458
6.718844 4.645352 4.635311
6.718868 4.650144 4.648421
6.718953 4.647271 4.657003
6.718675 4.64823 4.61413
6.718771 4.655863 4.658427
6.718941 4.656814 4.67423
6.718868 4.65396 4.666265
6.718989 4.662495 4.66683
6.718771 4.666265 4.66457
6.718699 4.670958 4.661551
6.718784 4.672829 4.650144
6.718844 4.681205 4.631909
6.718784 4.683057 4.62301
6.71876 4.678421 4.61512
6.718687 4.683981 4.609162
6.718735 4.685828 4.60617
6.718651 4.682131 4.603168
6.718615 4.670021 4.592085
6.718615 4.674696 4.582925
6.718639 4.678421 4.569543
6.718626 4.662495 4.567468
6.718699 4.658711 4.559126
6.718602 4.654912 4.55598
6.71859 4.653008 4.553877
6.718602 4.654912 4.55703
6.718699 4.660605 4.559126
6.718651 4.660605 4.570579
6.718602 4.659658 4.577388
6.718663 4.660605 4.578826
6.718602 4.657763 4.578826
6.718615 4.660605 4.588024
6.718663 4.663439 4.593098
6.718663 4.669084 4.599152
6.718675 4.669084 4.607168
6.718687 4.667206 4.618086
6.718602 4.677491 4.642466
6.718699 4.688592 4.662495
6.718663 4.699571 4.670021
6.718651 4.683981 4.656814
6.718651 4.682131 4.636669
6.718699 4.688592 4.62791
6.718687 4.689511 4.628887
6.718663 4.695011 4.628887
6.718651 4.697749 4.628887
6.718615 4.70048 4.625953
6.718675 4.702297 4.631812
6.718615 4.70592 4.645352
6.718651 4.70953 4.650144
6.718651 4.70953 4.650144
6.718663 4.713127 4.654912
6.718639 4.719391 4.665324
6.718639 4.728272 4.673763
6.718602 4.727388 4.683057
6.718639 4.727388 4.683981
6.718615 4.727388 4.688592
6.718602 4.730921 4.702297
6.71859 4.744932 4.708629
6.71859 4.752728 4.706824
6.71859 4.747538 4.695011
6.71859 4.750136 4.680278
6.71859 4.755313 4.673763
6.71859 4.763028 4.678421
6.71859 4.766438 4.681205
6.71859 4.763882 4.683981
6.71859 4.764735 4.674696

[此贴子已经被作者于2007-5-5 19:08:26编辑过]

thank you !