Model averaging for generalized linear models in fragmentary data prediction

Figures & data

Table 1. An illustrative example for fragmentary data.

Subject	Y	$X_1$	$X_2$	$X_3$	$X_4$	$X_5$	$X_6$	$X_7$	$X_8$
1	*	*	*	*	*	*	*	*	*
2	*	*	*	*	*	*	*	*	*
3	*	*	*	*
4	*	*	*	*				*	*
5	*	*			*	*	*
6	*	*			*	*	*
7	*	*
8	*	*				*		*	*
9	*	*	*					*	*
10	*	*	*					*	*

* Means the datum is available.

Table 2. Response patterns and sample sizes for ADNI data.

	Data source
k	MMSE	CSF	PET	MRI	GENE	Sample size
1	*	*	*	*	*	409
2	*	*	*	*		368
3	*	*	*		*	40
4	*		*	*	*	105
5	*		*		*	86
6	*		*	*		53
7	*				*	53
8	*			*		56
					Total	1,170

* The datum is available.

Figure 1. The KLs of all the methods in 200 replications when $\text{β}=0.4\times (1,1/2,\dots ,1/p)$.

Figure 2. The KLs of all the methods in 200 replications when $\text{β}=0.1\times (1,1,\dots ,1)$.

Figure 3. The KLs of all the methods in 200 replications when $\text{β}=0.2\times (1/p,\dots ,1/2,1)$.

Figure 4. The KL loss of all the methods in 100 replications for ADNI data.