Hi everyone I am using the hts package and using an ARIMA model with an external regresor, the problem is that I change the forecast horizon and still have the same results. The files are uploaded in a google drive link here
x2<-structure(list(PERIODOAAAAWW = c(201901, 201902, 201903, 201904, 201905, 201906, 201907, 201908, 201909, 201910, 201911, 201912, 201913, 201914, 201915, 201916, 201917, 201918, 201919, 201920, 201921, 201922, 201923, 201924, 201925, 201926, 201927, 201928, 201929, 201930, 201931, 201932, 201933, 201934, 201935, 201936, 201937, 201938, 201939, 201940, 201941, 201942, 201943, 201944, 201945, 201946, 201947, 201948, 201949, 201950, 201951, 201952, 202001, 202002, 202003, 202004, 202005, 202006, 202007, 202008, 202009, 202010, 202011, 202012, 202013, 202014, 202015, 202016, 202017, 202018, 202019, 202020, 202021, 202022, 202023, 202024, 202025, 202026, 202027, 202028, 202029, 202030, 202031, 202032, 202033, 202034, 202035, 202036, 202037, 202038, 202039, 202040, 202041, 202042, 202043, 202044, 202045, 202046, 202047, 202048, 202049, 202050, 202051, 202052, 202101, 202102, 202103, 202104, 202105, 202106, 202107, 202108, 202109, 202110, 202111, 202112, 202113, 202114, 202115, 202116, 202117, 202118, 202119, 202120, 202121, 202122, 202123, 202124, 202125, 202126, 202127, 202128, 202129, 202130, 202131, 202132, 202133, 202134, 202135, 202136), cases = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.69, 2.77, 4.96, 5.95, 6.59, 7.1, 6.87, 7.27, 7.66, 8.02, 8.33, 8.5, 8.93, 9.21, 9.23, 9.71, 9.96, 10.13, 10.35, 10.63, 10.85, 11.03, 11.18, 11.26, 11.25, 11.13, 10.99, 10.86, 10.79, 10.78, 10.67, 10.87, 10.84, 10.89, 11.07, 11.08, 10.91, 10.83, 10.95, 11.04, 10.94, 9.73, 11.36, 11.74, 11.71, 11.56, 11.25, 10.95, 10.52, 10.35, 10.15, 10.07, 10.2, 10.5, 10.77, 11.11, 11.48, 11.65, 11.7, 11.68, 11.61, 11.54, 11.78, 11.96, 12.14, 12.13, 12.16, 12.3, 12.15, 11.95, 11.74, 11.3, 11.08, 10.64, 10.24, 9.97, 9.62, 9.43, 9.38)), row.names = c(NA, -140L), class = c("tbl_df", "tbl", "data.frame"))
The other dataset
df<-structure(list(A01 = c(1.4, 1.6, 0.7, 1.1, 1.1, 1.1, 2.1, 1.1, 1.4, 1.6, 1.1, 0.7, 1.4, 1.4, 1.1, 1.6, 2, 2, 1.8, 0.7, 1.8, 1.4, 1.6, 2, 1.4, 1.1, 1.6, 1.4, 1.4, 1.4, 1.4, 1.1, 2.1, 1.4, 1.8, 1.4, 1.6, 1.4, 1.1, 1.6, 0.7, 1.6, 0.7, 0.7, 1.4, 1.1, 1.4, 2, 0.7, 2, 1.4, 1.6, 1.6, 1.1, 0.7, 1.1, 1.4, 1.4, 1.1, 1.1, 1.1, 1.4, 1.4, 1.4, 1.1, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.1, 1.1, 1.4, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 0.7, 1.1, 1.1, 1.1, 0.7, 0.7, 1.1, 1.8, 0.7, 0.7, 0.7, 1.1, 1.1, 0.7, 1.4, 1.4, 0.7, 0.7, 1.4, 1.4, 1.4, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 0.7, 0.7, 1.1, 1.4, 1.4, 1.1, 0.7, 1.1, 1.6, 1.1, 0.7, 1.1, 1.1, 0.7, 0.7, 1.4, 1.4, 1.8, 1.1, 1.1, 1.6, 1.4, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7), A02 = c(3.7, 2.9, 3, 3, 2.8, 3.1, 3.8, 3.6, 3.3, 3.4, 3.3, 3.1, 3.2, 3.3, 3.3, 3.2, 3.3, 3.2, 3, 3.3, 3.2, 3.5, 3, 2.9, 3.3, 3.4, 3.6, 3.4, 3.5, 3.3, 3.5, 3.5, 3.2, 3.2, 3, 3.7, 3.3, 3.1, 3.3, 3.5, 3, 2.8, 3, 2.9, 3.1, 3.1, 3.1, 3.1, 3.1, 3.3, 3.1, 3.6, 3.5, 3.7, 3.1, 3.2, 3.2, 2.9, 3.3, 3.2, 2.9, 3.1, 3.2, 3.1, 2.3, 1.6, 2, 1.4, 1.6, 2.2, 1.8, 2.2, 2.3, 2.4, 2.8, 2.4, 2.6, 2.2, 2.1, 2.7, 2.9, 2.6, 2.7, 2.6, 2.8, 2.4, 2.1, 2.7, 2.6, 2.6, 2.1, 2.5, 3.1, 2, 2.4, 2.2, 2.2, 2.3, 2.6, 3, 2.7, 2.9, 2.7, 2.6, 1.6, 3.1, 3.1, 3, 3.4, 2.6, 3.1, 2.7, 2.4, 2.8, 2.8, 3, 2.5, 2.5, 2.9, 3, 2.9, 2.8, 3, 3.1, 2.4, 2.9, 3.1, 3.2, 3.4, 3.3, 2.7, 2.7, 2.4, 2.6, 2.8, 3.4, 2.9, 2.6, 3.1, 1.4), A03 = c(1.1, 0.7, 1.1, 1.1, 1.1, 1.4, 1.1, 1.6, 1.6, 0.7, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 0.7, 0.7, 1.6, 0.7, 1.6, 1.4, 0.7, 0.7, 1.4, 1.4, 1.4, 0.7, 1.4, 0.7, 1.1, 1.1, 0.7, 1.6, 0.7, 0.7, 1.1, 1.4, 1.4, 0.7, 0.7, 1.1, 1.4, 1.6, 1.1, 1.4, 1.1, 2, 0.7, 0.7, 1.1, 0.7, 1.8, 0.7, 1.8, 1.4, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 1.1, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 1.1, 1.1, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.4, 1.4, 0.7, 0.7, 0.7, 0.7, 0.7, 1.4, 1.4, 1.4, 1.4, 1.4, 1.1, 0.7, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 2, 1.1, 1.1, 0.7, 0.7, 0.7, 1.4, 1.4, 0.7, 1.4, 1.4, 1.6, 1.1, 1.4, 1.1, 1.4, 0.7), A04 = c(0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.6, 1.6, 1.8, 1.8, 0.7, 1.1, 1.1, 1.4, 1.4, 1.4, 1.4, 1.1, 1.1, 1.4, 1.4, 1.6, 1.6, 1.6, 1.6, 1.6, 1.6, 0.7, 0.7, 0.7, 0.7, 1.1, 1.4, 1.4, 1.4, 1.1, 1.1, 1.1, 1.8, 1.1, 1.4, 1.1, 1.4, 1.1, 1.4, 1.4, 1.1, 1.1, 0.7, 1.4, 0.7, 0.7, 0.7, 1.1, 1.1, 1.4, 1.4, 1.6, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.4, 1.4, 1.4, 1.4, 1.4, 0.7, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.6, 0.7, 0.7, 1.1, 0.7, 0.7, 0.7, 1.8, 1.1, 0.7, 0.7, 1.4, 1.4, 1.4, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 1.4, 1.4, 0.7, 0.7, 1.1, 0.7, 1.1, 1.1, 0.7, 1.4, 0.7, 0.7, 1.1, 0.7, 1.1, 1.1, 1.4, 1.1, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7), A05 = c(2.6, 2.3, 1.1, 1.8, 0.7, 2.2, 1.8, 1.6, 1.8, 2.6, 1.8, 1.8, 2.2, 1.8, 2.2, 1.8, 2.4, 1.6, 2.3, 1.4, 1.6, 2.1, 2, 2.4, 0.7, 2.1, 1.4, 2, 2, 2, 2, 2.2, 2.6, 1.8, 2.3, 2.5, 2.1, 1.6, 2.2, 2.2, 1.4, 2, 1.6, 2.4, 2.3, 2.5, 2.6, 2, 1.4, 1.8, 2.5, 2.9, 2.4, 3.3, 1.6, 1.6, 1.6, 2.1, 1.6, 1.8, 2.1, 1.1, 1.8, 1.4, 0.7, 1.1, 0.7, 1.4, 1.4, 0.7, 1.4, 1.6, 1.1, 0.7, 0.7, 1.4, 1.1, 1.4, 1.6, 1.1, 1.8, 0.7, 2, 1.6, 1.6, 1.6, 0.7, 2.4, 1.1, 1.1, 0.7, 1.1, 2.3, 2, 2.2, 1.6, 2.3, 1.8, 1.8, 1.1, 1.6, 1.6, 1.6, 1.6, 0.7, 1.1, 1.6, 1.8, 1.8, 2.1, 2.8, 2.8, 2.4, 1.6, 1.8, 1.4, 1.8, 1.6, 1.8, 1.1, 1.8, 1.6, 1.6, 1.1, 1.1, 1.8, 2.1, 0.7, 1.6, 1.4, 2.3, 1.6, 2, 1.4, 1.8, 1.6, 1.6, 1.6, 2, 1.4), B01 = c(6.8, 6.4, 6.4, 6.4, 6.5, 6.5, 6.5, 6.4, 6.6, 6.5, 6.5, 6.5, 6.5, 6.6, 6.5, 6.2, 6.6, 6.6, 6.6, 6.6, 6.5, 6.6, 6.6, 6.6, 6.5, 6.5, 6.6, 6.6, 6.6, 6.7, 6.8, 7, 6.7, 6.5, 6.6, 6.6, 6.6, 6.7, 6.6, 6.7, 6.5, 6.6, 6.6, 6.7, 6.7, 6.9, 6.6, 6.8, 6.8, 6.8, 6.9, 6.7, 6.8, 6.9, 6.5, 6.5, 6.5, 6.5, 6.5, 6.5, 6.5, 6.4, 6.4, 6.1, 4.7, 4.9, 4.8, 5.1, 5.3, 5.5, 5.6, 5.8, 5.8, 5.7, 5.8, 6, 6, 6, 6.1, 6.1, 5.9, 5.9, 6.2, 6, 6.1, 6.1, 6.2, 6.2, 6.3, 6.3, 6.3, 6.3, 6.3, 6.1, 6.4, 6.3, 6.3, 6.3, 6.4, 6.4, 6.6, 6.4, 6.5, 6, 4, 6.1, 6.1, 6.4, 6.4, 6.4, 6.3, 6.3, 6.3, 6.5, 6.5, 6.5, 6.4, 6.1, 6.1, 6.2, 6.2, 6.3, 6.3, 6.4, 6.4, 6.5, 6.5, 6.4, 6.5, 6.6, 6.6, 6.5, 6.4, 6.5, 6.5, 6.6, 6.5, 6.7, 6.4, 5.4 ), B02 = c(4.6, 4, 3.8, 4.2, 4.2, 4.2, 4.1, 4.2, 4.4, 4.2, 4.3, 4.3, 3.9, 4.1, 4.2, 4, 4, 4.2, 4.1, 4, 4.2, 4, 4.1, 4.2, 4.3, 4, 4.1, 4.3, 4.5, 4.1, 4.2, 4.2, 4.3, 4.1, 4.3, 4.3, 4.3, 4.3, 4.1, 4.3, 4.1, 4.2, 4, 4.4, 4.3, 4, 3.9, 4.1, 4.5, 4.4, 4.7, 4.5, 4.4, 4.6, 4.4, 4, 4.1, 4, 4, 4.1, 4, 4, 4.1, 3.5, 2.7, 2.8, 2.7, 2.6, 2.6, 3.3, 3.2, 3.4, 3, 2.7, 3.3, 3.6, 3.7, 2.8, 3.4, 3.7, 3.6, 3.6, 3.6, 3.7, 3.6, 2.9, 3.8, 3.5, 3.6, 3.6, 3.6, 3.7, 3.5, 3.7, 3.9, 3.6, 3.9, 3.8, 3.7, 4, 4, 3.6, 3.6, 3.5, 2.4, 3.7, 3.8, 3.8, 3.7, 3.7, 3.7, 3.8, 4, 3.9, 3.5, 3.7, 3.8, 3.7, 4.1, 3.9, 3.5, 3.9, 3.5, 3.9, 3.7, 3.6, 4, 3.9, 4, 3.9, 3.6, 4, 4.1, 3.8, 4, 4.1, 3.9, 3.8, 4.1, 3), B03 = c(4.8, 4.8, 3.8, 3.8, 3.6, 3.8, 3.7, 3.6, 4.1, 4.1, 4, 4, 4, 4, 3.7, 3.9, 4, 4, 4, 4, 4, 4, 3.7, 3.8, 4, 3.7, 3.7, 3.6, 4.2, 3.9, 4, 3.5, 3.8, 3.7, 3.7, 4, 3.5, 3.5, 3.5, 3.8, 3.4, 3.8, 3.4, 4, 3.9, 3.9, 4.1, 4, 3.7, 3.7, 3.7, 4, 4.5, 4.9, 3.8, 3.7, 3.5, 3.7, 3.4, 3.6, 3.4, 3.3, 3.3, 2.9, 2.6, 2.2, 1.8, 2.3, 2.7, 2.4, 2.4, 2.6, 2.8, 3.1, 2.8, 3, 2.9, 2.9, 2.8, 3.4, 3.5, 2.9, 3, 2.9, 3, 3.1, 3.5, 3.3, 3.5, 3.4, 3.3, 3.6, 3.2, 3.6, 3.7, 3.4, 3.4, 3.3, 3.5, 3.5, 3.6, 4, 3.8, 3.1, 2.1, 3.2, 3.7, 3.7, 3.7, 3.8, 3.1, 3.1, 3.6, 3.1, 2.8, 3, 3.2, 3.4, 3.3, 3, 3.5, 3.3, 3.1, 3.4, 3.4, 3.1, 3.3, 3.2, 3.7, 3.2, 3.4, 3.8, 3.4, 3.5, 3.6, 3.1, 3.4, 3.4, 3.3, 2.6), B04 = c(7.9, 7.6, 7.7, 7.8, 7.9, 7.9, 8, 7.9, 8, 8, 8, 8, 7.9, 8, 7.9, 7.4, 8, 8, 8, 7.9, 7.9, 7.9, 7.8, 7.9, 7.8, 7.8, 7.9, 7.9, 7.9, 7.9, 7.9, 7.9, 7.9, 7.9, 8, 8, 7.9, 7.9, 7.9, 8, 7.8, 8, 7.9, 8, 7.9, 8, 7.9, 8, 8.1, 8.1, 8.1, 7.8, 8, 8.2, 7.8, 7.8, 7.8, 7.8, 7.8, 7.8, 7.8, 7.8, 7.7, 7.3, 6, 6.2, 6.1, 6.4, 6.7, 6.9, 7.1, 7.2, 7.3, 7.3, 7.4, 7.3, 7.3, 7.4, 7.4, 7.5, 7.3, 7.3, 7.5, 7.4, 7.4, 7.4, 7.5, 7.5, 7.5, 7.5, 7.5, 7.6, 7.6, 7.5, 7.6, 7.6, 7.6, 7.5, 7.6, 7.6, 7.7, 7.6, 7.6, 7.3, 5.5, 7.4, 7.4, 7.6, 7.6, 7.7, 7.7, 7.7, 7.7, 7.8, 7.8, 7.8, 7.7, 7.5, 7.7, 7.5, 7.6, 7.6, 7.7, 7.8, 7.8, 7.7, 7.8, 7.7, 7.8, 7.8, 7.8, 7.8, 7.8, 7.8, 7.9, 7.8, 7.8, 7.7, 7.8, 6.7), B05 = c(5, 4.4, 4.3, 4.6, 4.5, 4.4, 4.5, 4.6, 4.6, 4.8, 4.5, 4.5, 4.4, 4.4, 4.4, 4.1, 4.4, 4.5, 4.4, 4.3, 4.5, 4.3, 4.3, 4.4, 4.6, 4.9, 4.9, 4.7, 4.8, 4.6, 4.6, 4.6, 4.5, 4.6, 4.7, 4.7, 4.7, 4.6, 4.6, 4.6, 4.7, 4.5, 4.6, 4.7, 4.6, 4.4, 4.5, 4.6, 4.9, 4.6, 4.8, 4.7, 5, 5.2, 4.6, 4.7, 4.6, 4.4, 4.6, 4.7, 4.5, 4.6, 4.6, 4, 3.3, 3.3, 3.2, 3.3, 3.5, 3.7, 3.7, 3.9, 4.1, 4.1, 4.3, 4.3, 4.2, 4.1, 4.4, 4.3, 4.3, 4.1, 4.2, 4.1, 4.2, 4, 4.3, 4.5, 4.5, 4.3, 4.1, 4.4, 4.4, 4.4, 4.7, 4.4, 4.4, 4.6, 4.5, 4.5, 4.5, 4.5, 4.6, 4.3, 3.1, 4.7, 4.5, 4.7, 4.6, 4.6, 4.5, 4.5, 4.4, 4.3, 4.3, 4.4, 4.2, 4.5, 4.5, 4.5, 4.3, 4.2, 4.5, 4.8, 4.6, 4.5, 4.9, 4.6, 4.6, 4.7, 4.8, 4.6, 4.6, 4.7, 4, 4.4, 4.3, 4.4, 4.5, 3.6), B06 = c(4.8, 4, 4.3, 4.1, 4.5, 4.1, 4.2, 4.1, 4.1, 4.5, 4.2, 4.5, 4.4, 4.6, 4.4, 4.2, 4.3, 4.4, 4.4, 4.4, 4.4, 4.2, 4.5, 4.7, 4.5, 4.4, 4.4, 4.7, 4.4, 4.3, 4.5, 4.5, 4.4, 4.5, 4.3, 4.5, 4.4, 4.6, 4.8, 4.5, 4.4, 4.5, 4.7, 4.7, 4.6, 4.5, 4.6, 4.6, 4.9, 4.8, 4.8, 4.9, 4.8, 5.1, 4.7, 4.6, 4.6, 4.4, 4.4, 4.2, 4.4, 4.4, 4.3, 4, 3.1, 3.1, 3.1, 3.4, 3.7, 3.8, 4, 3.9, 4.1, 4, 4.1, 4.2, 4.1, 4.3, 4.3, 4.2, 4.3, 4, 3.9, 4, 4, 4.1, 3.7, 4, 3.8, 4.2, 3.9, 4.1, 4.2, 4, 4.4, 4, 4.4, 4.2, 4.4, 4.2, 4.4, 4.1, 4.2, 4, 2, 4.2, 4.3, 4.4, 4.4, 4.6, 4.4, 4.4, 4.4, 4.3, 4.3, 4.3, 4.3, 3.9, 4.4, 4.4, 4.3, 4, 4.2, 4.4, 4.3, 4.1, 4.4, 4.3, 4.4, 4.3, 4.4, 4.2, 4.3, 4.4, 4.4, 4.3, 4.2, 4.2, 4.2, 2.9 ), B07 = c(4.4, 3.8, 3.7, 3.8, 3.6, 4, 3.8, 3.7, 3.8, 4, 4, 3.9, 4, 3.8, 3.7, 3.8, 3.8, 4, 3.7, 3.7, 3.9, 4, 3.7, 4.2, 3.9, 4.1, 4.1, 4.1, 4, 3.9, 4, 4, 4, 4, 3.9, 3.6, 3.8, 3.9, 3.9, 4.1, 3.9, 3.8, 3.9, 4, 3.9, 4.1, 3.8, 3.9, 4.2, 4, 4.1, 4.2, 4.5, 4.4, 4.1, 4.1, 4.1, 4.1, 3.9, 4.1, 4, 4, 3.8, 3.6, 1.6, 2.2, 2.5, 2.6, 2.6, 2.6, 2.6, 3.4, 2.9, 2.9, 3.1, 3.6, 3.4, 2.9, 3.5, 3.7, 3.3, 3.5, 3.7, 3.6, 3.4, 3.3, 3.3, 3.6, 3.9, 3.7, 3.8, 3.3, 3.6, 3.3, 3.8, 3.6, 3.4, 3.8, 3.9, 3.6, 3.8, 3.4, 3.6, 3.6, 2.7, 3.3, 3.7, 3.8, 4.2, 4, 4, 4, 3.8, 3.8, 4, 3.7, 4, 3.7, 3.7, 4, 3.8, 3.8, 3.9, 3.8, 3.5, 3.7, 3.9, 3.5, 3.9, 4, 4.1, 3.7, 4.1, 3.9, 3.8, 4, 4, 3.6, 3.6, 2.8), B08 = c(4.3, 4.2, 4.5, 4.4, 4.3, 4.2, 4.4, 4.2, 4.3, 4.2, 4.2, 4.1, 4, 4, 4.1, 3.9, 4.1, 4.3, 4.3, 4.2, 4.1, 4.2, 4.1, 4, 4, 4.2, 4.1, 4, 4.2, 4.2, 4, 4.3, 4.5, 4.3, 4.4, 4.4, 4.4, 4.5, 4.4, 4.5, 4.2, 4.4, 4.4, 4.4, 4.4, 4.5, 4.4, 4.5, 4.5, 4.8, 4.6, 4.3, 4.7, 4.6, 4.3, 4.3, 4.3, 4.1, 4.1, 4.1, 4.1, 4, 4.1, 3.4, 2.5, 2.5, 2.5, 2.9, 2.7, 2.7, 3.3, 3.1, 3.6, 3.5, 3.5, 3.4, 3.5, 3.3, 3.9, 3.6, 3.9, 3.9, 3.8, 4.1, 4, 3.8, 4.3, 3.8, 4.1, 4.2, 4.1, 4.1, 4, 4, 4.1, 4.2, 4, 4.1, 4.2, 4.3, 4.2, 4.2, 4.2, 3.7, 2.5, 3.8, 4.1, 4.1, 4.1, 4.3, 4.4, 4.1, 4, 3.8, 4.1, 4.2, 4.2, 4.2, 4.2, 4.2, 4.2, 4.2, 4.1, 4.2, 3.8, 4.2, 4.4, 3.9, 4.5, 3.8, 4.1, 4.3, 4.4, 4.1, 4.1, 4.3, 4.4, 4.3, 4.3, 3.3), B09 = c(5.7, 5.2, 5.2, 5.4, 5.3, 5.3, 5.4, 5.4, 5.3, 5.6, 5.4, 5.4, 5.4, 5.5, 5.5, 5.2, 5.4, 5.3, 5.3, 5.3, 5.3, 5.4, 5.3, 5.3, 5.4, 5.2, 5.3, 5.3, 5.4, 5.3, 5.4, 5.2, 5.3, 5.3, 5.5, 5.3, 5.4, 5.4, 5.4, 5.4, 5.3, 5.3, 5.5, 5.5, 5.5, 5.5, 5.5, 5.6, 5.7, 5.6, 5.6, 5.6, 5.8, 5.9, 5.7, 5.5, 5.6, 5.3, 5.3, 5.3, 5.3, 5.3, 5.1, 4.9, 3.7, 3.9, 3.7, 4, 3.9, 4.5, 4.6, 4.7, 4.7, 4.6, 5.2, 4.8, 4.7, 5, 5.1, 4.9, 5.1, 5.1, 5.2, 5, 5.2, 5, 5, 4.9, 5.2, 5, 5, 5.1, 5, 4.9, 5.1, 5.1, 5.1, 5.2, 5.1, 5.1, 5.2, 5.2, 5.2, 5, 3.6, 5.2, 5.1, 5.3, 5.3, 5.4, 5.4, 5.3, 5.3, 5.4, 5.4, 5.3, 5.4, 5, 5.4, 5.5, 5.3, 5.2, 5.2, 5.5, 5.3, 5.3, 5.4, 5.3, 5.2, 5.4, 5.4, 5.4, 5.5, 5.3, 5.4, 5.3, 5.4, 5.3, 5.3, 3.9), B10 = c(5.2, 4.6, 4.8, 4.7, 4.6, 4.6, 4.9, 4.6, 4.8, 4.7, 4.8, 4.9, 4.9, 4.7, 4.9, 4.7, 4.7, 4.9, 4.9, 4.8, 4.9, 4.8, 4.7, 5.2, 4.8, 5.1, 5, 4.8, 4.7, 4.7, 4.8, 4.6, 4.8, 4.9, 4.9, 4.8, 4.6, 4.7, 4.7, 4.7, 4.8, 5, 4.7, 4.8, 4.7, 4.7, 4.9, 4.8, 5, 4.7, 4.7, 5, 5.4, 5.4, 4.5, 4.7, 4.4, 4.7, 4.6, 4.7, 4.4, 4.6, 4.6, 4.1, 3, 2.8, 3.3, 3.5, 3.5, 3.8, 3.7, 4.2, 4, 4, 4.3, 4.4, 4.4, 4.3, 4.5, 4.4, 4.5, 4.2, 4.5, 4.1, 4.4, 4.4, 4.3, 4.7, 4.6, 4.8, 4.4, 4.6, 4.7, 4.3, 4.5, 4.7, 4.5, 4.7, 4.6, 4.7, 4.5, 4.5, 4.7, 4.4, 3.2, 4.6, 4.5, 4.7, 4.6, 4.9, 4.8, 4.8, 4.8, 4.6, 4.7, 4.9, 4.6, 4.5, 4.7, 4.6, 4.6, 4.4, 4.5, 4.7, 4.7, 4.7, 4.8, 4.9, 4.9, 5, 5, 4.7, 4.8, 4.7, 4.8, 4.8, 4.9, 4.7, 4.6, 3.9 ), C01 = c(5.9, 5.5, 5.7, 5.8, 5.7, 5.7, 5.6, 6, 6.2, 5.9, 5.8, 5.7, 5.6, 5.6, 5.6, 5.3, 5.6, 5.7, 5.7, 5.6, 5.6, 5.6, 5.6, 5.7, 5.6, 5.6, 5.4, 5.5, 5.5, 5.5, 5.7, 5.6, 5.6, 5.5, 5.6, 5.7, 5.6, 5.7, 5.6, 5.7, 5.7, 5.8, 5.6, 5.6, 5.6, 5.8, 5.6, 5.7, 5.9, 5.9, 5.8, 5.7, 5.9, 6.1, 5.8, 5.7, 5.7, 5.5, 5.8, 6.1, 5.8, 5.7, 5.4, 5.3, 4.7, 4.5, 4.5, 4.8, 4.8, 4.9, 4.9, 5.1, 5, 5.1, 5.2, 5.1, 4.8, 4.8, 5, 5.3, 5.2, 5.2, 5.5, 5.3, 5.3, 5.4, 5.3, 5.4, 5.3, 5.4, 5.3, 5.3, 5.3, 5.3, 5.4, 5.4, 5.3, 5.4, 5.5, 5.7, 5.6, 5.5, 5.6, 5.1, 3.6, 5.4, 5.5, 5.5, 5.4, 5.5, 5.5, 5.3, 5.4, 5.4, 5.4, 5.5, 5.4, 5.2, 5.2, 5.3, 5.3, 5.3, 5.5, 5.5, 5.3, 5.5, 5.4, 5.4, 5.6, 5.5, 5.6, 5.5, 5.5, 5.4, 5.5, 5.6, 5.6, 5.5, 5.7, 4.6), C02 = c(5.2, 5, 4.8, 4.8, 5, 4.9, 4.9, 4.9, 4.9, 5, 5, 4.9, 5, 4.9, 4.7, 4.8, 4.8, 5, 4.7, 5, 4.9, 5, 4.9, 5.1, 5, 4.9, 4.9, 4.8, 4.8, 4.8, 4.9, 4.8, 4.7, 4.9, 4.8, 5, 5, 5, 4.9, 5.1, 4.6, 5.1, 5, 4.9, 5.3, 5.3, 4.9, 5, 5.4, 4.9, 5.1, 5.1, 5.5, 5.3, 4.9, 4.9, 4.7, 4.9, 4.6, 4.9, 4.9, 4.9, 4.8, 4.3, 2.9, 3.1, 3.5, 3.7, 3.8, 3.9, 4, 4.2, 4.1, 4.2, 4.1, 4.2, 4.4, 4.3, 4.3, 4.5, 4.6, 4.5, 4.6, 4.4, 4.5, 4.6, 4.7, 4.6, 4.4, 4.6, 4.7, 4.6, 4.6, 4.6, 4.8, 4.6, 4.6, 4.6, 4.5, 4.9, 4.9, 4.7, 4.6, 4.6, 3.4, 4.7, 4.7, 4.9, 4.8, 4.7, 4.8, 4.7, 4.7, 4.8, 4.8, 4.9, 4.8, 4.8, 4.7, 4.9, 4.9, 4.6, 4.7, 4.6, 4.9, 4.6, 4.5, 4.5, 4.7, 4.8, 4.7, 4.6, 4.7, 4.7, 4.7, 4.7, 4.6, 4.7, 4.4, 3.9), C03 = c(4.3, 3.9, 4.2, 4.2, 4.3, 4.4, 4.3, 4.3, 4.1, 4.3, 4.5, 4.2, 4.2, 4.4, 4.5, 3.8, 4.9, 4.5, 4.2, 4.4, 4.4, 4.3, 4.3, 4.5, 4.3, 4.3, 4.3, 4.2, 4.2, 4.3, 4.4, 4.6, 4.3, 4.3, 4.2, 4.2, 4.3, 4.4, 4.3, 4.3, 4.3, 4.3, 4.3, 4.4, 4.3, 4.5, 4.4, 4.4, 4.6, 4.4, 4.6, 4.3, 4.8, 4.6, 4.7, 4.4, 4.2, 4.1, 4.4, 4.3, 4.2, 4.1, 4.1, 4.2, 3.2, 3.3, 3.4, 3.2, 3.5, 3.7, 3.5, 3.7, 3.5, 3.8, 3.9, 3.7, 3.6, 3.9, 4.1, 3.8, 3.9, 3.7, 3.8, 3.6, 3.6, 3.7, 3.9, 3.9, 3.7, 3.8, 3.4, 3.7, 3.8, 3.6, 3.9, 3.9, 3.9, 3.6, 4.1, 4.1, 4.3, 4.2, 4.2, 3.6, 2.6, 4, 3.9, 4, 3.9, 4.2, 4.3, 4.1, 4.1, 4.3, 4.3, 4.2, 4.4, 4.4, 4.3, 4.1, 4.3, 3.9, 4, 4.2, 4.1, 4.1, 4.3, 4.4, 4.4, 4.5, 4.4, 4.3, 4.3, 4.2, 4, 4.3, 4.3, 4.1, 4.2, 3.2), C04 = c(4, 3.7, 3.8, 4.1, 4.1, 3.9, 3.9, 4.2, 4, 3.6, 3.9, 4, 3.9, 3.8, 3.6, 3.5, 3.5, 4, 3.8, 3.6, 3.7, 3.4, 3.7, 3.8, 3.8, 3.6, 3.6, 3.7, 3.2, 3.7, 3.6, 3.9, 4.1, 3.7, 3.8, 3.7, 3.9, 4, 3.9, 3.8, 3.4, 3.3, 3.7, 3.7, 3.9, 3.5, 3.7, 4.1, 4, 3.9, 3.8, 3.8, 4, 4, 3.9, 3.6, 4, 3.9, 3.6, 3.6, 4, 3.7, 3.5, 3.4, 2.4, 2.1, 2.2, 2.5, 2.8, 3, 3.2, 3.3, 2.9, 3.3, 2.8, 2.9, 3.1, 3.1, 3.5, 3, 2.9, 3.2, 3, 3.1, 3.2, 3.5, 3.2, 3.5, 3.5, 3.5, 3.4, 3.5, 3.7, 3.4, 3.6, 3.7, 3.4, 3.5, 3.5, 3.3, 3.1, 3.9, 3.8, 3.3, 1.8, 3.3, 3.5, 3.6, 3.4, 3.5, 3.5, 3.6, 3.6, 3.7, 3.9, 3.8, 3.8, 3.5, 3.9, 3.8, 3.4, 3.7, 3.6, 4, 3.7, 2.9, 3.5, 3.8, 3.8, 3.8, 3.8, 3.5, 3, 3.6, 3.3, 3.5, 3.4, 2.9, 3.3, 2.4), C05 = c(3.8, 3.6, 3.3, 3.6, 3.4, 3.6, 3.6, 3.5, 3.7, 3.6, 3.7, 3.6, 3.7, 3.9, 3.4, 3.3, 3.6, 3.8, 3.3, 3.5, 3.5, 3.3, 3.7, 3.9, 3.7, 3.4, 3.5, 4.1, 3.9, 3.6, 3.8, 3.8, 3.9, 3.6, 3.4, 3.5, 3.6, 3.8, 3.4, 3.8, 3.8, 3.8, 3.7, 4, 3.4, 3.9, 3.7, 3.9, 4.1, 3.7, 3.9, 3.5, 3.6, 3.9, 3.8, 3.9, 3.8, 3.7, 3.8, 3.6, 3.6, 3.6, 3.8, 3, 3.3, 2.6, 2.6, 3, 2.9, 3, 2.9, 3.1, 3.3, 3.1, 3.5, 3, 3.3, 3.5, 3.3, 3.2, 3.3, 3.5, 3.1, 2.9, 3.3, 3.4, 3.4, 3.3, 3.3, 2.9, 3, 3.2, 3.1, 3.1, 3.3, 3.7, 3.7, 3, 3.4, 3.7, 3.7, 3.4, 3, 3.3, 1.8, 3.3, 3.4, 3.5, 3.3, 3.3, 3.9, 3.7, 3.6, 3.7, 3.3, 3.4, 3.5, 3.1, 3.6, 3.3, 3.3, 3.1, 3.6, 3.3, 3.4, 3.2, 3.3, 3.4, 3.7, 3.1, 3.5, 3.4, 3.5, 3.1, 3.5, 3.3, 3.2, 3.2, 3.4, 2.1 ), C06 = c(5, 4.6, 4.4, 4.3, 4.2, 4.4, 4.3, 4.4, 4.4, 4.4, 4.6, 4.4, 4.2, 4.2, 4.5, 4.1, 4.4, 4.2, 4.4, 4.2, 4.2, 4.4, 4.4, 4.2, 4.4, 4.3, 4.3, 4.3, 4.3, 4.6, 4.6, 4.4, 4.2, 4.4, 4.6, 4.4, 4.5, 4.2, 4.2, 4.2, 4.5, 4.1, 4.2, 4.3, 4.4, 4.3, 4.4, 4.4, 4.7, 4.6, 4.4, 4.5, 4.7, 4.8, 4, 4.4, 4.5, 4.3, 4.3, 4.3, 4.4, 4.4, 4.3, 4.1, 2.8, 2.6, 3.3, 3.3, 3.4, 3.2, 3.3, 3.6, 3.6, 3.4, 3.6, 3.8, 3.5, 3.3, 3.6, 3.8, 3.8, 3.8, 3.8, 4.1, 3.6, 3.5, 3.9, 3.7, 3.8, 3.9, 3.9, 4.1, 4, 4, 4.1, 4.2, 4.1, 4, 4, 3.9, 3.9, 4, 4.2, 3.5, 3.3, 4.3, 4.1, 4.1, 3.9, 4.2, 4.1, 4.1, 4.2, 4.2, 4, 4.1, 4.3, 4, 3.9, 4, 3.9, 4.1, 4, 4.4, 4.3, 4, 4.4, 4.2, 4.3, 4.3, 4.3, 4.3, 4.4, 3.9, 4.4, 4.1, 4.4, 3.9, 4.1, 3.1), C07 = c(2.4, 2.3, 2.1, 2.5, 1.8, 2.3, 2.3, 2.7, 2, 2, 2.2, 2.1, 2.1, 2.1, 1.1, 2.1, 2, 2, 1.6, 2.3, 1.6, 1.6, 2.5, 2.2, 2.1, 2.1, 2, 2.1, 2.9, 2.1, 1.6, 2.2, 1.4, 2.1, 0.7, 1.8, 2.2, 2.2, 1.8, 2.2, 1.6, 2.3, 2.4, 1.6, 1.6, 2.1, 2.5, 2.2, 2.5, 2.3, 2.2, 2.4, 2.5, 2.3, 1.8, 1.4, 2.1, 1.6, 1.6, 2.2, 2.6, 1.6, 2.2, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 1.1, 1.1, 1.6, 1.6, 0.7, 1.1, 1.1, 1.4, 0.7, 0.7, 0.7, 1.4, 0.7, 0.7, 1.6, 1.4, 1.4, 0.7, 0.7, 0.7, 1.8, 2, 2, 1.4, 1.1, 1.8, 1.4, 1.6, 1.4, 1.4, 2, 1.8, 1.8, 1.6, 1.4, 0.7, 0.7, 2, 2.2, 1.8, 1.8, 0.7, 2, 2.2, 2.1, 2, 2, 1.1, 1.8, 1.4, 1.4, 0.7, 0.7, 1.1, 1.6, 2.1, 2.1, 0.7, 2.3, 2.3, 2.3, 1.8, 1.1, 1.6, 1.4, 0.7, 2.1, 1.8, 1.6, 2.2, 1.4 ), C08 = c(4.2, 3.8, 4.5, 4, 3.7, 4.1, 3.7, 3.8, 3.9, 3.6, 3.8, 3.7, 3.7, 3.3, 3.8, 4, 4, 3.7, 3.7, 3.8, 3.6, 3.6, 3.7, 3.5, 3.7, 3.7, 3.5, 3.9, 3.7, 3.7, 3.6, 3.7, 3.8, 3.9, 3.7, 3.8, 3.8, 4, 3.8, 3.8, 3.6, 3.5, 3.6, 3.7, 4.1, 3.9, 3.8, 3.7, 3.7, 4, 4.1, 3.9, 4.2, 4, 4.3, 4.1, 3.7, 3.9, 3.7, 3.3, 3.9, 3.9, 3.7, 3.9, 3, 2.2, 2.3, 3, 3.1, 2.9, 2.9, 3.3, 2.9, 3.1, 3.2, 3.2, 3.2, 3.1, 3, 3.7, 3.4, 3.4, 3.3, 3.2, 3.3, 3, 3.3, 3.3, 3.3, 3.4, 3.1, 3.3, 3.5, 3.4, 3, 3.7, 3.3, 2.9, 3.1, 3.3, 3, 3.5, 3.5, 3.2, 2, 3.3, 3.6, 3.5, 3.1, 3.5, 3.3, 3.5, 3.4, 3.5, 3.3, 3.6, 3.1, 4, 3.3, 3.7, 3.3, 3.6, 3.3, 3.6, 3.3, 3.3, 3.3, 3.7, 3.6, 3.3, 3.4, 3.5, 3.7, 3.7, 3.5, 3.4, 3.6, 3.2, 3.1, 2.8), D01 = c(2.7, 2.1, 2.3, 1.6, 2, 2.5, 1.8, 1.6, 2.1, 1.6, 2.6, 2, 1.6, 1.6, 2, 2.5, 2.2, 2.2, 2.4, 2.4, 2.1, 2, 2.6, 2.1, 2.6, 2.4, 2.7, 2.5, 2.3, 2.8, 2.4, 2.6, 2.2, 1.6, 2.5, 2.3, 2.7, 2.9, 2.9, 2.8, 2, 2.3, 2.7, 2.3, 2.4, 2.6, 2.1, 2.8, 3, 2.8, 2.1, 2.1, 2.1, 2.5, 2.4, 2.9, 2, 2.2, 2, 2.2, 2.5, 2.1, 2.4, 2.4, 0.7, 1.1, 1.1, 1.4, 0.7, 1.8, 1.4, 1.4, 1.4, 1.6, 2.1, 0.7, 1.4, 1.8, 1.1, 0.7, 2.1, 2.1, 1.8, 1.1, 2.4, 2.1, 1.8, 1.1, 1.6, 1.4, 2.3, 2.6, 2.2, 2, 2.8, 1.6, 2, 1.4, 2.1, 2.4, 2.1, 2.1, 2.3, 1.1, 0.7, 2, 2.1, 1.8, 1.8, 1.1, 1.4, 1.4, 2.1, 2.4, 2.2, 2.1, 2.8, 2.4, 2.7, 2.5, 2.3, 2.1, 1.1, 1.8, 1.6, 1.1, 1.6, 1.8, 1.6, 1.6, 1.8, 2.2, 2.4, 2.1, 2.5, 2.2, 2.3, 1.8, 2, 1.1), D02 = c(4, 3.6, 3.1, 3.3, 3.3, 3.4, 3.2, 3.5, 3.2, 3.4, 2.8, 3.5, 3.3, 3.3, 3.4, 2.5, 3.4, 3.6, 3.4, 3.5, 3.3, 3.4, 3, 3.2, 3.2, 3.2, 3.5, 3.4, 3.2, 3.4, 3.1, 3.5, 3.3, 3.6, 3.5, 3.5, 3.4, 3.6, 3.4, 3.4, 3.2, 3.7, 3.7, 3.5, 3.7, 3.7, 3.8, 3.7, 4, 3.9, 3.5, 3.3, 4.2, 4.1, 3.6, 3.6, 3.5, 3.1, 3.1, 3, 3.3, 3.2, 2.6, 2.6, 1.6, 2, 1.1, 2.2, 2.4, 2.1, 2.8, 2.3, 2.6, 2.9, 3, 2.6, 2.8, 2.8, 3.1, 2.9, 2.9, 3, 3, 2.8, 2.8, 3.1, 3, 3.2, 3.2, 2.9, 3.1, 3.4, 3.3, 3.3, 3.3, 3.3, 3.5, 3.3, 3.6, 3.8, 3.3, 3.3, 3.5, 3.4, 2.6, 3.7, 3.8, 3.5, 3.4, 3.2, 3.3, 3.2, 3, 3.1, 3.5, 3.3, 3.1, 3.5, 3.6, 3.6, 3.6, 2.9, 3.1, 3.4, 3.1, 3.5, 3.6, 3.5, 3, 2.8, 3.2, 3.1, 3, 3.3, 3.4, 3.3, 3.4, 3.5, 3.7, 2), D03 = c(5.2, 4.7, 4.5, 4.5, 4.8, 4.8, 4.7, 4.7, 4.7, 4.8, 4.5, 4.6, 5, 4.8, 4.8, 4.5, 4.6, 4.6, 4.6, 4.7, 4.8, 4.8, 4.7, 4.7, 4.6, 4.6, 4.6, 4.7, 4.7, 4.7, 4.9, 4.6, 4.9, 4.7, 4.7, 4.6, 4.5, 4.5, 4.6, 4.7, 4.6, 4.8, 4.5, 4.8, 4.7, 5, 4.8, 4.9, 4.8, 4.9, 4.9, 4.8, 5.3, 5.3, 4.7, 4.6, 4.5, 4.7, 4.3, 4.4, 4.5, 4.5, 4.4, 3.9, 3.1, 3.4, 2.9, 3.4, 3.4, 3.6, 3.7, 4, 3.9, 3.8, 4, 4.2, 4.2, 4, 4.1, 4.4, 4.4, 4.1, 4.5, 4.3, 4.2, 3.8, 4.1, 4.2, 4.1, 4, 4.3, 4.2, 4.3, 4.2, 4.6, 4.4, 4.4, 4.4, 4.4, 4.5, 4.6, 4.4, 4.6, 4.4, 2.1, 4.4, 4.3, 4.5, 4.3, 4.6, 4.6, 4.5, 4.4, 4.6, 4.5, 4.5, 4.6, 4.4, 4.4, 4.4, 4.5, 4, 4.5, 4.4, 4.4, 4.4, 4.4, 4.5, 4.8, 4.7, 4.8, 4.6, 4.6, 4.4, 4.6, 4.5, 4.6, 4.6, 4.5, 3.5), D04 = c(0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.4, 1.4, 1.4, 1.4), D05 = c(1.4, 0.7, 0.7, 0.7, 0.7, 0.7, 1.4, 1.4, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.6, 0.7, 0.7, 0.7, 1.4, 1.8, 1.4, 1.4, 1.1, 0.7, 0.7, 0.7, 1.1, 1.1, 1.4, 0.7, 1.1, 0.7, 1.4, 0.7, 0.7, 0.7, 1.1, 0.7, 1.1, 0.7, 1.1, 0.7, 0.7, 0.7, 1.1, 1.4, 0.7, 1.8, 1.1, 1.1, 0.7, 1.1, 0.7, 0.7, 0.7, 1.8, 1.4, 0.7, 0.7, 1.6, 0.7, 0.7, 1.6, 1.6, 1.6, 1.1, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 1.1, 1.1, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 1.1, 1.1, 0.7, 0.7, 1.6, 1.4, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 1.1, 0.7, 0.7, 0.7, 0.7, 1.1, 0.7, 0.7, 0.7, 0.7), E01 = c(4.8, 4.5, 4.7, 4.4, 4.7, 4.6, 4.6, 4.6, 4.6, 4.6, 4.8, 4.5, 4.5, 4.4, 4.6, 4.7, 4.8, 4.7, 4.6, 4.5, 4.7, 4.9, 4.7, 4.9, 4.6, 4.7, 4.6, 4.6, 4.5, 4.6, 4.6, 4.5, 4.5, 4.4, 4.5, 4.7, 4.8, 4.6, 4.6, 4.8, 4.6, 4.4, 4.6, 4.8, 4.9, 4.7, 4.8, 5, 4.8, 4.7, 4.7, 4.7, 4.8, 5, 4.8, 4.7, 4.7, 4.5, 4.2, 4.4, 4.4, 4.6, 4.2, 3.9, 2.8, 3.2, 2.5, 3.2, 3.3, 3.4, 3.5, 3.7, 3.7, 3.7, 3.7, 3.5, 4, 3.8, 3.9, 4, 4, 3.8, 3.9, 4.1, 3.9, 3.9, 4, 4, 4.1, 3.9, 4.3, 4.2, 4.2, 4, 4.3, 4.3, 4.2, 4.3, 4.2, 4.3, 4.3, 4, 4.4, 4.1, 2.8, 4.2, 4.4, 4, 4.1, 4.4, 4.2, 4.4, 4.5, 4.4, 4.4, 4.3, 4.4, 4.2, 4.4, 4.4, 4.3, 4.2, 4.3, 4.3, 4.4, 4.6, 4.6, 4.2, 4.6, 4.5, 4.4, 4.5, 4.3, 4.6, 4.3, 4.3, 4.4, 4.3, 4.4, 3.2), E02 = c(3.4, 3.5, 3, 2.8, 2.5, 3.1, 2.6, 2.8, 3.3, 3.1, 3.3, 2.3, 2.6, 3.4, 2.6, 2.6, 2.9, 2.8, 3, 2.6, 3, 2.5, 2.9, 2.4, 2.6, 2.6, 3, 2.8, 2.8, 2.2, 3.1, 2.6, 2.8, 2.8, 2.9, 2.8, 2.6, 3.1, 2.9, 2.8, 2.8, 2.8, 2.7, 2.8, 2.6, 2.8, 3, 3.2, 2.7, 2.7, 3.1, 2.9, 3, 2.8, 2.5, 2.6, 2.8, 2.8, 2.4, 2.1, 2.4, 2.8, 2.4, 2, 1.6, 1.6, 2, 1.1, 2, 2, 0.7, 1.6, 1.4, 1.1, 1.8, 1.6, 1.1, 1.1, 1.1, 1.1, 2, 2.5, 2.2, 1.8, 2, 1.8, 2.2, 2.3, 2, 1.4, 2.3, 2.6, 2.1, 1.8, 2.3, 2.6, 2.2, 1.4, 2.2, 2, 2.7, 2.4, 2.2, 2.2, 0.7, 2.6, 2.8, 2.7, 2.2, 3, 2.8, 2.6, 2.7, 2.7, 2.6, 2.4, 2.6, 2.2, 2.4, 2.6, 2.3, 2.9, 2.2, 2.6, 2.6, 1.4, 2.5, 2.3, 3.1, 2.3, 2.8, 2.8, 2.7, 2.6, 2.1, 2.6, 2.6, 2.5, 2.7, 1.1), E03 = c(5.3, 5, 4.5, 4.6, 4.6, 4.7, 4.6, 4.6, 4.7, 4.8, 4.7, 4.6, 4.6, 4.6, 4.8, 4.4, 4.7, 4.7, 4.7, 4.5, 4.5, 4.6, 4.6, 4.7, 4.5, 4.7, 4.6, 4.6, 4.6, 4.7, 4.9, 4.8, 4.7, 4.9, 4.8, 4.8, 5, 4.9, 4.8, 4.7, 4.6, 4.7, 4.8, 4.7, 4.9, 4.7, 4.7, 4.9, 4.8, 4.8, 4.7, 4.9, 5.8, 5.8, 4.7, 4.8, 4.6, 4.7, 4.5, 4.6, 4.6, 4.4, 4.4, 4.2, 3.2, 3.1, 2.8, 3, 3.4, 3.6, 3.7, 3.8, 4, 3.8, 4.2, 3.9, 4, 3.9, 4.2, 4.4, 4.2, 4.2, 4.2, 4.1, 4, 4, 4.5, 4.3, 4.3, 4.3, 4.4, 4.6, 4.5, 4.4, 4.7, 4.5, 4.5, 4.5, 4.5, 4.3, 4.6, 4.5, 4.6, 4.1, 3.1, 4.2, 4.4, 4.5, 4.3, 4.5, 4.6, 4.5, 4.5, 4.6, 4.6, 4.6, 4.7, 4.5, 4.6, 4.6, 4.6, 4.5, 4.7, 4.8, 4.6, 4.7, 4.9, 4.7, 4.8, 4.8, 4.9, 4.6, 4.5, 4.5, 4.7, 4.7, 4.6, 4.8, 4.5, 3.4), E04 = c(6.5, 5.8, 6, 6.1, 6.1, 6.2, 6.3, 6.2, 6.3, 6.4, 6.2, 6.2, 6.1, 6.2, 6.3, 5.9, 6.3, 6.4, 6.3, 6.2, 6.3, 6.3, 6.1, 6.2, 6.2, 6.1, 6.1, 6.2, 6.2, 6.2, 6.1, 6.2, 6.3, 6.2, 6.2, 6.2, 6.2, 6.2, 6.2, 6.3, 6.2, 6.3, 6.3, 6.2, 6.2, 6.3, 6.2, 6.3, 6.5, 6.4, 6.4, 6.6, 6.2, 6.4, 6.2, 6.2, 6.3, 6.2, 6.1, 6, 6.1, 6.2, 6.1, 5.6, 4.6, 4.5, 4.5, 4.7, 5, 5, 5, 5.3, 5.2, 5.4, 5.4, 5.6, 5.6, 5.5, 5.8, 5.7, 5.7, 5.7, 5.8, 5.7, 5.8, 5.6, 5.8, 5.9, 5.9, 5.7, 5.8, 5.9, 6, 5.8, 6, 6.1, 6, 6.1, 6, 6, 6.1, 6.1, 5.9, 5.6, 4.1, 5.8, 5.6, 6, 6, 6.1, 6.1, 6, 6, 6, 6.1, 6.2, 6, 6, 6.2, 6, 6, 6, 5.8, 6, 6.2, 6.1, 6.3, 6.3, 6.2, 6.2, 6.1, 6.1, 6.1, 6, 6.1, 6, 6, 6, 6, 5)), row.names = c(NA, -140L), class = c("tbl_df", "tbl", "data.frame"))
Now the code:
library(tibble)
library(tidyverse)
library(hts)
x2<-read_csv(X2.csv)
df<-read_csv(csv.csv)
dfts<- ts(df, frequency=365.25/7, start=c(2019,1))
x2 <- ts(x2, frequency=365.25/7, start=c(2019,1))
x <- hts(dfts, characters = c(1,2))
data <- window(x, start = 2019.000, end = 2021.166)
test <- window(x, start = 2021.185)
lvl=2
FPer=8
set.seed(123)
fore <- forecast(data, h = FPer, method = "bu", fmethod = "arima", lambda=0, xreg = window(x2, end = 2021.166), newxreg = window(x2, start = 2021.185))
accu<- as.data.frame(accuracy(fore, test, levels = lvl))
accu$row_mean <- rowMeans(accu, na.rm=TRUE)
accu <- rev(accu)
accu <- accu[,1, drop=FALSE]
accu
Then I get the result following MAPE
MAPE 13.4301521
After that, I change the forecast horizon h to 2 and I get the same results
MAPE 13.4301521
Any help will be appreciated, I guess the forecast function is not properly coded.
Cheers
If you look at your
foreobject, you will see it has 25 forecasts, matching the number of rows in thenewxregargument. Thehargument is being ignored because you are passing anewxregargument.