Occupancy Estimation in a Subway Station Using Bayesian Simulation Based on Carbon Dioxide and Particle Concentrations : Table 2

Table 2: Summary of Bayesian inference results during weekdays.

Analysis condition		Mean of a Day
Analysis condition			10/4	10/5	10/6	10/7	10/8
Gaussian	Static	Error(%)	35.7	27.6	31.0	38.0	33.3
	Static	Range	25	23	24	33	23
	Dynamic	Error(%)	21.4	24.1	24.2	24.2	30.0
	Dynamic	Range	11	10	11	13	11
Possion	Dynamic	Error(%)	22.1	23.8	27.1	24.4	32.6
Possion	Dynamic	Range	7	7	8	7	7
PM₁₀		Error(%)	-	-	-	20.4	-
PM₁₀		Range	-	-	-	6	-