用spwmatrix 如何生成“经济”空间权重矩阵（WE）

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收藏 2010-08-14

在spwmatrix 命令中，有一条是说可以生成“经济”空间权重矩阵（WE）。
      wtype(bin|inv|econ|invecon|socnet|socecon) indicates whether binary,
      distance decay, economic distance, inverse economic distance, social
      network, or socio-economic spatial weights should be created.
同时里面也给出了个例子：
4) Generate an economic distance spatial weights matrix using employment  as the economic variable
   run: spwmatrix gecon latitude longitude, wn(wecon) wtype(econ)  econvar(employment) rowstand.

于此，我就用自己的数据（数据里面包括 latitude， longitude，GDP），我是打算用GDP作为权重的，例子中是用employment的。
我运行后出现以下字母(红色的)
      _=invalid name



   SOS ，不知道这是为什么。？？？

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jzbd

2010-8-14 20:49:07

自己顶一下。

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zhaowill

2010-8-15 12:09:26

把数据附上。

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jzbd

2010-8-15 18:49:22

楼上的，数据已经在这了。SOS，帮忙运算一下吧。麻烦了。

数据都是很简单的，一个是经度变量，一个是纬度变量，一个是ID，另外一个变量时GDP。
现在来生成经济空间矩阵，但就是出来。我是安装help 做的。

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W.xls

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zhangtao

2010-8-16 17:16:29

. spwmatrix gecon latitude longitude, wname(wknn5) knn(5) rowstand

Nearest neighbor (5) spatial weights matrix calculated successfully and
>  the following actions taken:

- Spatial weights matrix  created as Stata object(s): wknn5.

- N.B.: Stata spatial weights matrix, wknn5, can be used as if it was
> created by the user-written command spatwmat.

- Spatial weights matrix has been row-standardized.

. spwmatrix socio village_id, wname(socecon_wght) row wtype(socecon)

spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 500)  r
> (3958.761) row
N.B.: Elements of 2 rows sum up to zero, weighting matrix was not row-s
> tandardized
These rows are:
  28
  29
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.
Binary distance spatial weights matrix calculated successfully and the
> following actions taken:
- Spatial weights matrix  created as Stata object(s): wbin.
- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

为什么不出结果呢？

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zhangtao

2010-8-16 17:19:30

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zhangtao

2010-8-16 17:24:23

spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 150)  r
> (3958.761) row

N.B.: Elements of 22 rows sum up to zero, weighting matrix was not row-
> standardized

These rows are:
  4
  5
  6
  7
  8
  9
  11
  12
  13
  14
  16
  17
  18
  19
  20
  21
  22
  23
  28
  29
  30
  31
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
> (3958.761) row

N.B.: Elements of 24 rows sum up to zero, weighting matrix was not row-
> standardized

These rows are:
  4
  5
  6
  7
  8
  9
  10
  11
  12
  13
  14
  16
  17
  18
  19
  20
  21
  22
  23
  25
  28
  29
  30
  31
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
> (358.761) row

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

- Spatial weights matrix has been row-standardized.

.
. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
> (1358.761) row

N.B.: Elements of 6 rows sum up to zero, weighting matrix was not row-s
> tandardized

These rows are:
  9
  11
  21
  28
  29
  30
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
> (558.761) row

N.B.: Elements of one row sum up to zero, weighting matrix was not row-
> standardized

This row is:
  28
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
> (158.761) row

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

- Spatial weights matrix has been row-standardized.

. list

   +---------------------------------------------------------+
   | provid       proveng longit~e latitude    gdp |
   |---------------------------------------------------------|
  1. |    1          Anhui       119       31 69.4842 |
  2. |    2       Beijing    116.43    39.91 72.8565 |
  3. |    3       Chongqing    106.56    29.56    71.73 |
  4. |    4          Fujian       118       26 68.5743 |
  5. |    5          Gansu       102       38 67.2363 |
   |---------------------------------------------------------|
  6. |    6       Guangdong       113       23 72.521 |
  7. |    7       Guangxi       109       24 68.7223 |
  8. |    8       Guizhou       107       27 64.2908 |
  9. |    9          Hainan    109.5    19.2 70.0111 |
10. |    10          Hebei    114.3    38.02 70.3524 |
   |---------------------------------------------------------|
11. |    11    Heilongjiang       128       48 66.9732 |
12. |    12          Henan       114       34 70.1546 |
13. |    13          Hubei       112       31 67.2547 |
14. |    14          Hunan       112       28 66.9335 |
15. |    15       Jiangsu    120.25    31.75 65.678 |
   |---------------------------------------------------------|
16. |    16       Jiangxi       116       28 71.3742 |
17. |    17          Jilin    126.55    43.85 66.1062 |
18. |    18       Liaoning       123       41 67.9495 |
19. |    19    Nei Mongol    111.41    40.48 70.2189 |
20. |    20       Ningxia       106       37 66.9432 |
   |---------------------------------------------------------|
21. |    21       Qinghai       96       36 60.5695 |
22. |    22       Shaanxi       109       35 67.4042 |
23. |    23       Shandong       118       36 70.571 |
24. |    24       Shanghai    121.29    31.14 74.9035 |
25. |    25          Shanxi       112       37 68.9713 |
   |---------------------------------------------------------|
26. |    26       Sichuan       105    29.83 66.3282 |
27. |    27       Tianjin    117.12    39.02 72.3214 |
28. |    28       Xinjiang       82       38 59.638 |
29. |    29 Xizang Zizhiqu       88       29 62.5905 |
30. |    30          Yunnan       101       24 63.4897 |
   |---------------------------------------------------------|
31. |    31       Zhejiang       120       29    71.78 |
   +---------------------------------------------------------+

.

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zhangtao

2010-8-17 08:47:15

spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 500)  r
>  (3958.761) row

N.B.: Elements of 2 rows sum up to zero, weighting matrix was not row-s
> tandardized

These rows are:
  28
  29
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. spwmatrix gecon latitude longitude, wn(wbin)  wtype(bin) db(0 100)  r
>  (3958.761) row

N.B.: Elements of 24 rows sum up to zero, weighting matrix was not row-
> standardized

These rows are:
  4
  5
  6
  7
  8
  9
  10
  11
  12
  13
  14
  16
  17
  18
  19
  20
  21
  22
  23
  25
  28
  29
  30
  31
You might want to rethink your weights structure criteria.
Use nearstat to obtain distance information and a neighbor count
for your distance-cutoff or distance band.

Binary distance spatial weights matrix calculated successfully and the
> following actions taken:

- Spatial weights matrix  created as Stata object(s): wbin.

- N.B.: Stata spatial weights matrix, wbin, can be used as if it was c
> reated by the user-written command spatwmat.

. mat list  wbin

symmetric wbin[31,31]
         0 0 0  100  100  100  100  100  100  100  100  100
SWMDist 0
Yes 0 0
Yes 0 0 0
Yes 0 0 0 0
Yes 0 0 0 0 0
Yes 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 1 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 1 0 0 0 0 0 0 0 0 0
Yes 0 1 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0

      100  100  100  100  100  100  100  100  100  100  100  100
Yes 0
Yes 0 0
Yes 0 0 0
Yes 0 0 0 0
Yes 0 0 0 0 0
Yes 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 1 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0 0 0 0 0 0

      100  100  100  100  100  100  100
Yes 0
Yes 0 0
Yes 0 0 0
Yes 0 0 0 0
Yes 0 0 0 0 0
Yes 0 0 0 0 0 0
Yes 0 0 0 0 0 0 0

. list

   +---------------------------------------------------------+
   | provid       proveng longit~e latitude    gdp |
   |---------------------------------------------------------|
  1. |    1          Anhui       119       31 69.4842 |
  2. |    2       Beijing    116.43    39.91 72.8565 |
  3. |    3       Chongqing    106.56    29.56    71.73 |
  4. |    4          Fujian       118       26 68.5743 |
  5. |    5          Gansu       102       38 67.2363 |
   |---------------------------------------------------------|
  6. |    6       Guangdong       113       23 72.521 |
  7. |    7       Guangxi       109       24 68.7223 |
  8. |    8       Guizhou       107       27 64.2908 |
  9. |    9          Hainan    109.5    19.2 70.0111 |
10. |    10          Hebei    114.3    38.02 70.3524 |
   |---------------------------------------------------------|
11. |    11    Heilongjiang       128       48 66.9732 |
12. |    12          Henan       114       34 70.1546 |
13. |    13          Hubei       112       31 67.2547 |
14. |    14          Hunan       112       28 66.9335 |
15. |    15       Jiangsu    120.25    31.75 65.678 |
   |---------------------------------------------------------|
16. |    16       Jiangxi       116       28 71.3742 |
17. |    17          Jilin    126.55    43.85 66.1062 |
18. |    18       Liaoning       123       41 67.9495 |
19. |    19    Nei Mongol    111.41    40.48 70.2189 |
20. |    20       Ningxia       106       37 66.9432 |
   |---------------------------------------------------------|
21. |    21       Qinghai       96       36 60.5695 |
22. |    22       Shaanxi       109       35 67.4042 |
23. |    23       Shandong       118       36 70.571 |
24. |    24       Shanghai    121.29    31.14 74.9035 |
25. |    25          Shanxi       112       37 68.9713 |
   |---------------------------------------------------------|
26. |    26       Sichuan       105    29.83 66.3282 |
27. |    27       Tianjin    117.12    39.02 72.3214 |
28. |    28       Xinjiang       82       38 59.638 |
29. |    29 Xizang Zizhiqu       88       29 62.5905 |
30. |    30          Yunnan       101       24 63.4897 |
   |---------------------------------------------------------|
31. |    31       Zhejiang       120       29    71.78 |
   +---------------------------------------------------------+

.

.

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zwa222

2010-8-21 18:31:58

看来,关于经济矩阵,问题依然存在啊!纠结中...........

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陈清鸿

2010-10-7 15:46:09

是啊我也正需要那

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gdczlhd

2011-1-10 15:11:08

mark一下谢谢

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xge2000

2011-1-11 08:11:01

i lllllllllllllllllllllllllike it

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tutu0319

2012-4-12 20:01:18

出来没有啊

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sx19891989

2012-5-13 01:14:23

mark一下

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浅夏荒冬

2012-6-27 15:36:22

spwmatrix gecon latitude longitude, wn(wecon) wtype(econ) econvar(gdp) rowstand.

于此，我就用自己的数据（数据里面包括 latitude， longitude，GDP），用GDP作为权重的，运行后出现以下字母(红色的)
_=invalid name
我尝试着做，也是 _=invalid name
请问楼主怎么解决这个问题的？