Table 3.

Influence of default transition parameters p_stay and p_skip

pstay	pskip	MCorr	NCorr	MIdn	NIdn
.10	.24	.852	.822	.689	.679
.12	.28		.818		.679
.12	.24		.818		.679
.11	.22		.818		.679
.12	.22		.817		.679
.11	.24		.817		.679
.12	.30		.815		.679
.12	.26		.815		.679
.11	.26		.815		.68
.09	.26		.815		.679
.09	.24		.815		.679
.12	.32		.814		.679
.10	.30		.814		.679
.10	.22		.814		.679
.09	.22		.814		.679
.11	.28		.813		.679
.11	.32		.812		.679
.10	.32		.812		.679
.09	.28		.812		.679
.10	.28		.811		.679
.10	.26		.811		.68
.11	.30		.81		.679
.09	.32		.805		.679
.09	.30		.804		.679

All runs on 1000 human pcr reads, with double strand scaling with no transition parameter training (2ss-nott). Other columns: see Table 2.