Skip to main content

Table 8 MSE in the estimation of E(θ), keeping the total number of evaluations of the target fixed to L=KNT=2·105 in all algorithms, for the bivariate target in Section 6.2

From: A survey of Monte Carlo methods for parameter estimation

L=NKT=2·105
N Algorithm σ=1 σ=2 σ=5 σ=10 σ=20 σ=70
5 Standard PMC [95] 92.80 38.71 12.65 0.38 0.047 37.44
100   75.17 59.42 14.24 0.25 0.028 0.18
5·104   68.29 37.44 7.01 0.25 0.033 0.17
100 DM-PMC (K=1) 72.48 36.21 5.34 0.036 0.029 0.21
  GR-PMC (K=2) 69.41 26.23 3.09 0.022 0.028 0.17
  LR-PMC (K=2) 2.68 0.007 0.010 0.018 0.102 32.88
  GR-PMC (K=5) 67.04 17.44 0.11 0.013 0.023 0.15
  LR-PMC (K=5) 8.04 0.012 0.008 0.016 0.027 2.00
  GR-PMC (K=20) 61.58 15.13 0.42 0.012 0.024 0.14
  LR-PMC (K=20) 9.51 1.16 0.011 0.013 0.023 0.22
  GR-PMC (K=100) 64.94 12.50 0.08 0.015 0.026 0.18
  LR-PMC (K=100) 9.60 1.21 0.022 0.015 0.026 0.20
  GR-PMC (K=500) 58.49 9.63 0.08 0.014 0.024 0.16
  LR-PMC (K=500) 14.79 6.72 0.10 0.010 0.024 0.20
100 M-PMC [96] 71.39 81.33 18.14 0.058 0.031 0.14
10   84.14 81.68 6.49 0.76 0.024 4.60
100 SMC [286] 77.00 76.5 15.98 0.79 0.068 0.86
5·104   69.08 51.29 20.48 0.22 0.038 0.68
  DM-SMC (K=1) 70.95 42.40 1.91 0.039 0.027 0.19
  GR-SMC (K=5) 66.64 41.54 0.16 0.015 0.024 0.19
100 LR-SMC (K=5) 8.16 2.32 0.007 0.015 0.027 2.19
  GR-SMC (K=20) 65.48 37.91 0.10 0.013 0.025 0.19
  LR-SMC (K=20) 8.88 4.15 0.010 0.014 0.026 0.20
100 APIS (T=100) 0.0318 0.0011 0.0054 0.0129 0.0211 0.1794
  APIS (T=50) 0.0144 0.0007 0.0051 0.0131 0.0221 0.1772
  APIS (T=20) 0.0401 0.0006 0.0047 0.0136 0.0245 0.1732
  APIS (T=5) 0.0008 0.0005 0.0064 0.0149 0.0270 0.2076
  APIS (T=2) 0.0017 0.0116 0.0103 0.0182 0.0387 0.1844
1 AMIS (best) 112.70 107.85 44.93 0.7404 0.0121 0.0141
  AMIS (worst) 115.62 111.83 70.62 9.43 0.0871 18.62
  1. The best results for each value of σ are highlighted in bold-face