用r软件做分位数回归.docx
- 文档编号:3623813
- 上传时间:2022-11-24
- 格式:DOCX
- 页数:9
- 大小:17.73KB
用r软件做分位数回归.docx
《用r软件做分位数回归.docx》由会员分享,可在线阅读,更多相关《用r软件做分位数回归.docx(9页珍藏版)》请在冰豆网上搜索。
用r软件做分位数回归
分位数回归R(quantreg)
一、
如果你能能上国外的点击菜单上“程序包”——>“安装程序包”——>选择一个网站——>点击“quantreg”就能下载并安装。
如果你不能上网站,把我附件中的文件解压后,放入R\library的子目录下就可以了。
二、
用library(quantreg)调入,就可以作分位数回归了。
下面的命令帮助你熟悉quantreg.
>help(package="quantreg")
>help(rq)
三、下面是一个例子,或许对你有帮助。
data(engel)
engel
xy
1420.1577255.8394
2541.4117310.9587
3901.1575485.6800
4639.0802402.9974
5750.8756495.5608
6945.7989633.7978
7829.3979630.7566
8979.1648700.4409
91309.8789830.9586
101492.3987815.3602
11502.8390338.0014
12616.7168412.3613
13790.9225520.0006
14555.8786452.4015
15713.4412512.7201
16838.7561658.8395
17535.0766392.5995
18596.4408443.5586
19924.5619640.1164
20487.7583333.8394
21692.6397466.9583
22997.8770543.3969
23506.9995317.7198
24654.1587424.3209
25933.9193518.9617
26433.6813338.0014
27587.5962419.6412
28896.4746476.3200
29454.4782386.3602
30584.9989423.2783
31800.7990503.3572
32502.4369354.6389
33713.5197497.3182
34906.0006588.5195
35880.5969654.5971
36796.8289550.7274
37854.8791528.3770
381167.3716640.4813
39523.8000401.3204
40670.7792435.9990
41377.0584276.5606
42851.5430588.3488
431121.0937664.1978
44625.5179444.8602
45805.5377462.8995
46558.5812377.7792
47884.4005553.1504
481257.4989810.8962
492051.17891067.9541
501466.33301049.8788
51730.0989522.7012
52800.7990572.0807
531245.6964907.3969
541201.0002811.5776
55634.4002427.7975
56956.2315649.9985
571148.6010860.6002
581768.82361143.4211
592822.53302032.6792
60922.3548590.6183
612293.19201570.3911
62627.4726483.4800
63889.9809600.4804
641162.2000696.2021
651197.0794774.7962
66530.7972390.5984
671142.1526612.5619
681088.0039708.7622
69484.6612296.9192
701536.02011071.4627
71678.8974496.5976
72671.8802503.3974
73690.4683357.6411
74860.6948430.3376
75873.3095624.6990
76894.4598582.5413
771148.6470580.2215
78926.8762543.8807
79839.0414588.6372
80829.4974627.9999
811264.0043712.1012
821937.9771968.3949
83698.8317482.5816
84920.4199593.1694
851897.57111033.5658
86891.6824693.6795
87889.6784693.6795
881221.4818761.2791
89544.5991361.3981
901031.4491628.4522
911462.9497771.4486
92830.4353757.1187
93975.0415821.5970
941337.99831022.3202
95867.6427679.4407
96725.7459538.7491
97989.0056679.9981
981525.0005977.0033
99672.1960561.2015
100923.3977728.3997
101472.3215372.3186
102590.7601361.5210
103940.9218517.9196
104643.3571459.8177
1052551.6615863.9199
1061795.3226831.4407
1071165.7734534.7610
108815.6212392.0502
1091264.2066934.9752
1101095.4056813.3081
111447.4479263.7100
1121178.9742769.0838
113975.8023630.5863
1141017.8522645.9874
115423.8798319.5584
116558.7767348.4518
117943.2487614.5068
1181348.3002662.0096
1192340.61741504.3708
120587.1792406.2180
1211540.9741692.1689
1221115.8481588.1371
1231044.6843511.2609
1241389.7929700.5600
1252497.78601301.1451
1261585.3809879.0660
1271862.0438912.8851
1282008.85461509.7812
129697.3099484.0605
130571.2517399.6703
131598.3465444.1001
132461.0977248.8101
133977.1107527.8014
134883.9849500.6313
135718.3594436.8107
136543.8971374.7990
1371587.3480726.3921
1384957.81301827.2000
139969.6838523.4911
140419.9980334.9998
141561.9990473.2009
142689.5988581.2029
1431398.5203929.7540
144820.8168591.1974
145875.1716637.5483
1461392.4499674.9509
1471256.3174776.7589
1481362.8590959.5170
1491999.25521250.9643
1501209.4730737.8201
1511125.0356810.6772
1521827.4010983.0009
1531014.1540708.8968
154880.3944633.1200
1552432.39101424.8047
1561177.8547830.9586
1571222.5939925.5795
1581519.58111162.0024
159687.6638383.4580
160953.1192621.1173
161953.1192621.1173
162953.1192621.1173
163939.0418548.6002
1641283.4025745.2353
1651511.5789837.8005
1661342.5821795.3402
167511.7980418.5976
168689.7988508.7974
1691532.3074883.2780
1701056.0808742.5276
171387.3195242.3202
172387.3195242.3202
173410.9987266.0010
174832.7554614.7588
175614.9986385.3184
176887.4658515.6200
1771024.8177708.4787
1781006.4353734.2356
179726.0000433.0010
180494.4174327.4188
181748.6413429.0399
182987.6417619.6408
183788.0961400.7990
184831.7983620.8006
1851139.4945819.9964
186507.5169360.8780
187576.1972395.7608
188696.5991442.0001
189650.8180404.0384
190949.5802670.7993
191497.1193297.5702
192570.1674353.4882
193724.7306383.9376
194408.3399284.8008
195638.6713431.1000
1961225.7890801.3518
197715.3701448.4513
XX文库-让每个人平等地提升自我198800.4708577.9111
199975.5974570.5210
2001613.7565865.3205
201608.5019444.5578
202958.6634680.4198
203835.9426576.2779
204873.7375631.7982
205951.4432608.6419
206473.0022300.9999
207601.0030377.9984
208713.9979397.0015
209829.2984588.5195
210959.7953681.7616
2111212.9613807.3603
212958.8743696.8011
2131129.4431811.1962
2141943.04191305.7201
215539.6388442.0001
216463.5990353.6013
217562.6400468.0008
218736.7584526.7573
2191415.4461890.2390
2202208.78971318.8033
221636.0009331.0005
222759.4010416.4015
2231078.8382596.8406
224499.7510408.4992
2251020.0225775.0209
2261595.16111138.1620
227776.5958485.5198
2281230.9235772.7611
2291807.9520993.9630
230415.4407305.4390
231440.5174306.5191
232541.2006299.1993
233581.3599468.0008
234743.0772522.6019
2351057.6767750.3202
如果我们希望得到med[Y|X=x]=a+bx中位数回归,那么你可以用下面的命令:
fit1<-rq(y~x,tau=0.5,data=engel)
fit1中存放了你想得到的参数估计,因此你可直接用fit1调用:
fit1
Call:
rq(formula=y~x,tau=0.5,data=engel)
命令summary(fit1)会给你更多的结果:
Call:
rq(formula=y~x,tau=0.5,data=engel)
tau:
[1]0.5
Coefficients:
coefficientslowerbdupperbd
(Intercept)81.4822553.25915114.01156
x0.560180.487020.60199
用下面的命令可以得到残差的值:
r1<-resid(fit1)
r1
这是最简单,如果你想知道更详细的可查阅R网站上关于quantileregression的内容。
- 配套讲稿:
如PPT文件的首页显示word图标,表示该PPT已包含配套word讲稿。双击word图标可打开word文档。
- 特殊限制:
部分文档作品中含有的国旗、国徽等图片,仅作为作品整体效果示例展示,禁止商用。设计者仅对作品中独创性部分享有著作权。
- 关 键 词:
- 软件 位数 回归