Table 1: Prediction errors of the new improved parsimonious multivariate Markov chain model with original convergence condition in Example  2.


IPM1 when 31.1845* 31.0831* 29.8349* 29.8349* 31.0906* 31.0853*
IPM1 when 27.0472* 26.9434* 26.8745* 26.8745* 26.9486* 26.8462*
IPM1 when 22.8309* 22.7298* 22.7296* 22.7302* 22.7321* 22.7310*
IPM1 when 18.6215* 18.5266* 18.5256* 18.5256* 18.5282* 18.5211*
IPM1 when 14.3298* 14.2594* 14.2614* 14.2614* 14.2586* 14.2705*
IPM1 when 10.4531* 10.2961* 10.3231* 10.2962* 10.2795* 10.2971*
IPM1 when 9.9017 9.8994 9.8872 9.8879 9.8896 9.8552
IPM1 when 10.1173 10.1440 10.1255 10.1271 10.1283 10.0536
IPM1 when 10.3910 10.4131 10.3945 10.3886 10.3803 10.2726
IPM1 when 10.4059 10.4268 10.4059 10.4059 10.4059 10.2590