1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE mu 493.6769 0.01285 1.285e-05 3.564e-05 r[1] 0.8101 0.48421 4.842e-04 5.354e-04 r[2] 1.0698 0.69051 6.905e-04 9.878e-04 r[3] 0.8171 0.48464 4.846e-04 5.161e-04 r[4] 0.8903 0.53044 5.304e-04 5.713e-04 r[5] 0.8175 0.49282 4.928e-04 5.288e-04 r[6] 4.5338 3.03359 3.034e-03 4.704e-03 r[7] 1.1908 0.70179 7.018e-04 7.371e-04 r[8] 0.8121 0.48643 4.864e-04 5.035e-04 r[9] 2.0938 1.76421 1.764e-03 3.675e-03 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% mu 493.6497 493.6680 493.6778 493.6872 493.697 r[1] 0.3588 0.5322 0.6889 0.9332 1.986 r[2] 0.4098 0.6661 0.9014 1.2591 2.736 r[3] 0.3617 0.5381 0.6958 0.9420 1.999 r[4] 0.3928 0.5865 0.7584 1.0274 2.175 r[5] 0.3608 0.5370 0.6954 0.9426 2.007 r[6] 1.3815 2.7852 3.8487 5.4038 11.809 r[7] 0.5333 0.7871 1.0145 1.3696 2.905 r[8] 0.3644 0.5374 0.6922 0.9338 1.979 r[9] 0.4660 0.9894 1.6476 2.6319 6.396As we can see, at this point the most suspicious measurement is the 6-th of the complete list, as we can better judge from the quantiles indicating that, for example, there is only about 2.5% probability that
mu r[1] r[2] r[3] r[4] r[5] r[6] r[7] r[8] r[9] mu 1.00 -0.15 0.33 0.07 0.15 -0.01 0.40 -0.11 -0.10 -0.61 r[1] -0.15 1.00 -0.04 0.00 -0.02 0.01 -0.06 0.02 0.02 0.10 r[2] 0.33 -0.04 1.00 0.04 0.05 0.02 0.14 -0.03 -0.03 -0.20 r[3] 0.07 0.00 0.04 1.00 0.01 0.02 0.03 -0.01 0.00 -0.03 r[4] 0.15 -0.02 0.05 0.01 1.00 0.00 0.06 -0.02 -0.01 -0.09 r[5] -0.01 0.01 0.02 0.02 0.00 1.00 0.00 0.00 0.00 0.02 r[6] 0.40 -0.06 0.14 0.03 0.06 0.00 1.00 -0.04 -0.04 -0.25 r[7] -0.11 0.02 -0.03 -0.01 -0.02 0.00 -0.04 1.00 0.01 0.07 r[8] -0.10 0.02 -0.03 0.00 -0.01 0.00 -0.04 0.01 1.00 0.06 r[9] -0.61 0.10 -0.20 -0.03 -0.09 0.02 -0.25 0.07 0.06 1.00The