选择分段回归中的断点数

Selecting the number of breakpoints in segmented regression

我正在尝试为响应变量 Y 估计 X 中的多个断点。当我 运行 R 中的分段包时,如果我在 psi 中指定 1 个点,我会在 x=14 处得到 1 个估计断点如果我在 psi 中指定 2 个点,则语句和 x=6.5 和 x=11.4 处的两个估计点。如何确定 2 个断点是最优的还是 1 个断点是最优的?请查看下面的代码和输出:

指定 1 个断点:

segmented.glm(obj = fit.glm, seg.Z = ~x, psi = 10)

Estimated Break-Point(s):
                            Est. St.Err
psi1.x   14  2.691

Null     deviance: 230311  on 1509  degrees of freedom
Residual deviance: 175795  on 1480  degrees of freedom
AIC: 11531
Convergence attained in 0 iter. (rel. change 1.5525e-08)

> slope(fit.seg)
$x
            Est.  St.Err.   t value CI(95%).l CI(95%).u
slope1 -0.847880 0.097683 -8.679900   -1.0393  -0.65643
slope2  0.036962 0.574770  0.064308   -1.0896   1.16350

指定 2 个断点:

fit.seg<-segmented(fit.glm, seg.Z=~x, psi= c(6, 11))
 
Estimated Break-Point(s):
        Est. St.Err
psi1.x  6.562  1.771
psi2.x 11.398  1.660

Null     deviance: 230311  on 1509  degrees of freedom
Residual deviance: 175594  on 1478  degrees of freedom
AIC: 11533
Convergence attained in 1 iter. (rel. change 0)

> slope(fit.seg)
$x
           Est. St.Err.  t value CI(95%).l CI(95%).u
slope1 -0.56943 0.23681 -2.40460  -1.03360  -0.10530
slope2 -1.25180 0.38974 -3.21190  -2.01570  -0.48794
slope3 -0.17365 0.31700 -0.54781  -0.79495   0.44765

我使用了 seg.control 但不知道如何解释输出。 (基于 Muggeo,V.M.R。(2008)分段:一个 R 包,用于拟合具有折线关系的回归模型。R 新闻 8/1,20-25。)

> o <- segmented(fit.glm, seg.Z=~x, psi=NA, control=seg.control(display=FALSE, K=2))
Warning message:
max number of iterations (1) attained 
> slope(o)  # defaults to confidence level of 0.95 (conf.level=0.95)
$x
           Est. St.Err.  t value CI(95%).l CI(95%).u
slope1 -0.56943 0.23681 -2.40460  -1.03360  -0.10530
slope2 -1.25180 0.38974 -3.21190  -2.01570  -0.48794
slope3 -0.17365 0.31700 -0.54781  -0.79495   0.44765

> o <- segmented(fit.glm, seg.Z=~x, psi=NA, control=seg.control(display=FALSE, K=1))
Warning messages:
1: max number of iterations (1) attained 
2: max number of iterations (1) attained 
> slope(o)  # defaults to confidence level of 0.95 (conf.level=0.95)
$x
            Est.  St.Err.   t value CI(95%).l CI(95%).u
slope1 -0.847880 0.097683 -8.679900   -1.0393  -0.65643
slope2  0.036966 0.574770  0.064314   -1.0896   1.16350

任何人都可以帮我弄清楚如何确定 2 个断点是更好的估计值还是 1 个断点?

函数 selgmented()(也在 R 包 segmented 中)是 select 通过假设检验(例如分数检验)或 BIC 的“最佳”断点数的包装器。目前 selection 通过假设检验仅限于 0,1 或 2 个断点 selected。 亲切的问候, 维托