epoh 发表于 2012-4-30 15:47 
回复你的短信息.
#####
library(tsDyn)
就用你上面的例子得到了的结果,也存在不显著的系数:那么要不要进行处理呢:
> data=(lynx)
>
mod=lstar(log10(lynx), m=2, mTh=c(0,1), control=list(maxit=3000))
> phi1=mod$model.specific$coefficients[1:3]
> phi2=mod$model.specific$coefficients[4:6]
> gamma=mod$model.specific$coefficients[7]
> th=mod$model.specific$coefficients[8]
> z=mod$model.specific$thVar
> G=function(y,g,th) plogis(y, th, 1/g)
> tf=G(z,gamma,th)
> plot(z,tf)
> mod
> summary(mod)
Non linear autoregressive model
LSTAR model
Coefficients:
Low regime:
const1 phi1.1 phi1.2
0.4891014 1.2465399 -0.3664328
High regime:
const2 phi2.1 phi2.2
-1.0240758 0.4232669 -0.2546088
Smoothing parameter: gamma = 11.15
Threshold
Variable: Z(t) = + (0) X(t) + (1) X(t-1)
Value: 3.339
Residuals:
Min 1Q Median 3Q Max
-0.594820 -0.107360 0.014309 0.111098 0.510342
Fit:
residuals variance = 0.03805, AIC = -357, MAPE = 5.58%
Coefficient(s):
Estimate Std. Error t value Pr(>|z|)
const1 0.489101 0.204914 2.3869 0.0169929 *
phi1.1 1.246540 0.067871 18.3663 < 2.2e-16 ***
phi1.2 -0.366433 0.104301 -3.5132 0.0004427 ***
const2 -1.024076 2.430066 -0.4214 0.6734492
phi2.1 0.423267 0.172146 2.4588 0.0139415 *
phi2.2 -0.254609 0.585416 -0.4349 0.6636207
gamma 11.153834 10.004728 1.1149 0.2649120
th 3.339199 0.092748 36.0030 < 2.2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Non-linearity test of full-order LSTAR model against full-order AR model
F = 12.446 ; p-value = 1.3815e-05
Threshold
Variable: Z(t) = + (0) X(t) + (1) X(t-1)
在结果中,有不显著的系数:
phi2.2 (其P值 0.6636207);
如何去掉这个不显著的phi2.2呢?一直被这个问题纠结!
谢谢!