在下面给出的gls输出中,如何从gls对象中提取参数估计值1.000000 3.913972 10.684698 11.350910 26.476561 27.255072并将它们分配给另一个变量?
> m
X Y F
1 1 1.07 1
2 1 1.01 1
3 1 0.99 1
4 1 1.09 1
5 1 0.94 1
6 1 1.00 1
7 1 1.01 1
8 1 0.98 1
9 1 1.00 1
10 1 1.03 1
11 4 3.66 4
12 4 3.75 4
13 4 3.77 4
14 4 3.92 4
15 4 4.08 4
16 4 3.99 4
17 4 3.95 4
18 4 4.10 4
19 4 3.88 4
20 4 4.04 4
21 10 10.13 10
22 10 10.20 10
23 10 9.77 10
24 10 10.28 10
25 10 8.71 10
26 10 9.79 10
27 10 9.82 10
28 10 9.85 10
29 10 10.07 10
30 10 9.63 10
31 20 20.22 20
32 20 19.46 20
33 20 19.02 20
34 20 20.06 20
35 20 20.94 20
36 20 19.92 20
37 20 19.96 20
38 20 20.04 20
39 20 19.67 20
40 20 19.96 20
41 30 31.04 30
42 30 31.40 30
43 30 31.84 30
44 30 30.77 30
45 30 32.13 30
46 30 31.17 30
47 30 30.36 30
48 30 29.95 30
49 30 30.74 30
50 30 30.67 30
51 40 41.14 40
52 40 40.29 40
53 40 42.77 40
54 40 38.36 40
55 40 39.17 40
56 40 39.61 40
57 40 40.73 40
58 40 39.42 40
59 40 40.72 40
60 40 40.24 40
> Fit.gls <- gls(Y ~ X,weights=varIdent(form = ~ 1 | F),data=m)
> summary(Fit.gls)
Generalized least squares fit by REML
Model: Y ~ X
Data: m
AIC BIC logLik
78.96207 95.44562 -31.48104
Variance function:
Structure: Different standard deviations per stratum
Formula: ~1 | F
Parameter estimates:
1 4 10 20 30 40
1.000000 3.913972 10.684698 11.350910 26.476561 27.255072
答案 0 :(得分:2)
这会给你你想要的吗?
x <- Fit.gls$model
coef(x, unconstrained=FALSE)
# varStruct.4 varStruct.10 varStruct.20 varStruct.30 varStruct.40
# 3.913972 10.684698 11.350910 26.476561 27.255072