get_dictionary returns the indicators that can be extracted from "jSA" objects,
get_indicators extracts a list of indicators
jSA2R returns the corresponding "SA".
Arguments
- x
a
"jSA"object.- ...
characters containing the names of the indicators to extract.
- userdefined
a userdefined vector containing the names of additional output variables (see
user_defined_variables). Only used for"SA"objects.
Value
get_dictionary returns a vector of characters,
get_indicators returns a list containing the indicators that are extracted,
jSA2R returns a "SA" or a "regarima" object and
get_jspec returns a Java object.
Details
A "jSA" object is a list of three elements:
"result": the Java object containing the results of a seasonal adjustment or a pre-adjustment method."spec": the Java object containing the specification of a seasonal adjustment or a pre-adjustment method."dictionary": the Java object containing the dictionary of a seasonal adjustment or a pre-adjustment method. In particular, it contains all the user-defined regressors.
get_dictionary returns the list of indicators that can be extracted from a jSA object by the function get_indicators.
jSA2R returns the corresponding formatted seasonally adjusted ("SA" object) or RegARIMA ("regarima" object) model.
get_jspec returns the Java object that contains the specification of an object. Such object can be of type
"jSA", "X13", "TRAMO_SEATS" or "sa_item".
Examples
myseries <- ipi_c_eu[, "FR"]
mysa <- jx13(myseries, spec = "RSA5c")
get_dictionary(mysa)
#> [1] "y"
#> [2] "y_f"
#> [3] "t"
#> [4] "t_f"
#> [5] "sa"
#> [6] "sa_f"
#> [7] "s"
#> [8] "s_f"
#> [9] "i"
#> [10] "i_f"
#> [11] "mode"
#> [12] "preprocessing.model.span.start"
#> [13] "preprocessing.model.span.end"
#> [14] "preprocessing.model.span.n"
#> [15] "preprocessing.model.espan.start"
#> [16] "preprocessing.model.espan.end"
#> [17] "preprocessing.model.espan.n"
#> [18] "preprocessing.model.log"
#> [19] "preprocessing.model.adjust"
#> [20] "preprocessing.model.y"
#> [21] "preprocessing.model.y_f"
#> [22] "preprocessing.model.y_ef"
#> [23] "preprocessing.model.yc"
#> [24] "preprocessing.model.yc_f"
#> [25] "preprocessing.model.yc_ef"
#> [26] "preprocessing.model.l"
#> [27] "preprocessing.model.y_lin"
#> [28] "preprocessing.model.y_lin_f"
#> [29] "preprocessing.model.ycal"
#> [30] "preprocessing.model.ycal_f"
#> [31] "preprocessing.model.det"
#> [32] "preprocessing.model.det_f"
#> [33] "preprocessing.model.l_f"
#> [34] "preprocessing.model.l_b"
#> [35] "preprocessing.model.cal"
#> [36] "preprocessing.model.cal_f"
#> [37] "preprocessing.model.tde"
#> [38] "preprocessing.model.tde_f"
#> [39] "preprocessing.model.mhe"
#> [40] "preprocessing.model.mhe_f"
#> [41] "preprocessing.model.ee"
#> [42] "preprocessing.model.ee_f"
#> [43] "preprocessing.model.omhe"
#> [44] "preprocessing.model.omhe_f"
#> [45] "preprocessing.model.out(*)"
#> [46] "preprocessing.model.out_f"
#> [47] "preprocessing.model.out_i"
#> [48] "preprocessing.model.out_i_f"
#> [49] "preprocessing.model.out_t"
#> [50] "preprocessing.model.out_t_f"
#> [51] "preprocessing.model.out_s"
#> [52] "preprocessing.model.out_s_f"
#> [53] "preprocessing.model.reg"
#> [54] "preprocessing.model.reg_f"
#> [55] "preprocessing.model.reg_t"
#> [56] "preprocessing.model.reg_t_f"
#> [57] "preprocessing.model.reg_s"
#> [58] "preprocessing.model.reg_s_f"
#> [59] "preprocessing.model.reg_i"
#> [60] "preprocessing.model.reg_i_f"
#> [61] "preprocessing.model.reg_sa"
#> [62] "preprocessing.model.reg_sa_f"
#> [63] "preprocessing.model.reg_y"
#> [64] "preprocessing.model.reg_y_f"
#> [65] "preprocessing.model.reg_u"
#> [66] "preprocessing.model.reg_u_f"
#> [67] "preprocessing.model.fullresiduals"
#> [68] "preprocessing.model.lp"
#> [69] "preprocessing.model.ntd"
#> [70] "preprocessing.model.nmh"
#> [71] "preprocessing.model.td(*)"
#> [72] "preprocessing.model.easter"
#> [73] "preprocessing.model.nout"
#> [74] "preprocessing.model.noutao"
#> [75] "preprocessing.model.noutls"
#> [76] "preprocessing.model.nouttc"
#> [77] "preprocessing.model.noutso"
#> [78] "preprocessing.model.coefficients"
#> [79] "preprocessing.model.description"
#> [80] "preprocessing.model.covar"
#> [81] "preprocessing.model.pcovar"
#> [82] "preprocessing.model.fcasts(?)"
#> [83] "preprocessing.model.bcasts(?)"
#> [84] "preprocessing.model.lin_fcasts(?)"
#> [85] "preprocessing.model.lin_bcasts(?)"
#> [86] "preprocessing.model.efcasts(?)"
#> [87] "preprocessing.arima.parameters"
#> [88] "preprocessing.arima.p"
#> [89] "preprocessing.arima.d"
#> [90] "preprocessing.arima.q"
#> [91] "preprocessing.arima.bp"
#> [92] "preprocessing.arima.bd"
#> [93] "preprocessing.arima.bq"
#> [94] "preprocessing.likelihood.neffectiveobs"
#> [95] "preprocessing.likelihood.np"
#> [96] "preprocessing.likelihood.logvalue"
#> [97] "preprocessing.likelihood.adjustedlogvalue"
#> [98] "preprocessing.likelihood.ssqerr"
#> [99] "preprocessing.likelihood.aic"
#> [100] "preprocessing.likelihood.aicc"
#> [101] "preprocessing.likelihood.bic"
#> [102] "preprocessing.likelihood.bicc"
#> [103] "preprocessing.likelihood.ser"
#> [104] "preprocessing.likelihood.ser-ml"
#> [105] "preprocessing.residuals.res"
#> [106] "preprocessing.residuals.mean"
#> [107] "preprocessing.residuals.skewness"
#> [108] "preprocessing.residuals.kurtosis"
#> [109] "preprocessing.residuals.dh"
#> [110] "preprocessing.residuals.lb"
#> [111] "preprocessing.residuals.lb2"
#> [112] "preprocessing.residuals.seaslb"
#> [113] "preprocessing.residuals.bp"
#> [114] "preprocessing.residuals.bp2"
#> [115] "preprocessing.residuals.seasbp"
#> [116] "preprocessing.residuals.nruns"
#> [117] "preprocessing.residuals.lruns"
#> [118] "mstats.M(*)"
#> [119] "mstats.Q"
#> [120] "mstats.Q-M2"
#> [121] "decomposition.a1"
#> [122] "decomposition.a1a"
#> [123] "decomposition.a1b"
#> [124] "decomposition.a6"
#> [125] "decomposition.a7"
#> [126] "decomposition.a8"
#> [127] "decomposition.a8t"
#> [128] "decomposition.a8s"
#> [129] "decomposition.a8i"
#> [130] "decomposition.a9"
#> [131] "decomposition.a9sa"
#> [132] "decomposition.a9u"
#> [133] "decomposition.a9ser"
#> [134] "decomposition.b1"
#> [135] "decomposition.b2"
#> [136] "decomposition.b3"
#> [137] "decomposition.b4"
#> [138] "decomposition.b5"
#> [139] "decomposition.b6"
#> [140] "decomposition.b7"
#> [141] "decomposition.b8"
#> [142] "decomposition.b9"
#> [143] "decomposition.b10"
#> [144] "decomposition.b11"
#> [145] "decomposition.b12"
#> [146] "decomposition.b13"
#> [147] "decomposition.b14"
#> [148] "decomposition.b15"
#> [149] "decomposition.b16"
#> [150] "decomposition.b17"
#> [151] "decomposition.b18"
#> [152] "decomposition.b19"
#> [153] "decomposition.b20"
#> [154] "decomposition.c1"
#> [155] "decomposition.c2"
#> [156] "decomposition.c3"
#> [157] "decomposition.c4"
#> [158] "decomposition.c5"
#> [159] "decomposition.c6"
#> [160] "decomposition.c7"
#> [161] "decomposition.c8"
#> [162] "decomposition.c9"
#> [163] "decomposition.c10"
#> [164] "decomposition.c11"
#> [165] "decomposition.c12"
#> [166] "decomposition.c13"
#> [167] "decomposition.c14"
#> [168] "decomposition.c15"
#> [169] "decomposition.c16"
#> [170] "decomposition.c17"
#> [171] "decomposition.c18"
#> [172] "decomposition.c19"
#> [173] "decomposition.c20"
#> [174] "decomposition.d1"
#> [175] "decomposition.d2"
#> [176] "decomposition.d3"
#> [177] "decomposition.d4"
#> [178] "decomposition.d5"
#> [179] "decomposition.d6"
#> [180] "decomposition.d7"
#> [181] "decomposition.d8"
#> [182] "decomposition.d9"
#> [183] "decomposition.d10"
#> [184] "decomposition.d10a"
#> [185] "decomposition.d10b"
#> [186] "decomposition.d11"
#> [187] "decomposition.d11a"
#> [188] "decomposition.d12"
#> [189] "decomposition.d12a"
#> [190] "decomposition.d13"
#> [191] "decomposition.d14"
#> [192] "decomposition.d15"
#> [193] "decomposition.d16"
#> [194] "decomposition.d16a"
#> [195] "decomposition.d16b"
#> [196] "decomposition.d18"
#> [197] "decomposition.d19"
#> [198] "decomposition.d20"
#> [199] "decomposition.e1"
#> [200] "decomposition.e2"
#> [201] "decomposition.e3"
#> [202] "decomposition.e11"
#> [203] "decomposition.y_cmp"
#> [204] "decomposition.t_cmp"
#> [205] "decomposition.i_cmp"
#> [206] "decomposition.s_cmp"
#> [207] "decomposition.sa_cmp"
#> [208] "decomposition.y_cmp_f"
#> [209] "decomposition.t_cmp_f"
#> [210] "decomposition.i_cmp_f"
#> [211] "decomposition.s_cmp_f"
#> [212] "decomposition.sa_cmp_f"
#> [213] "decomposition.d9filter"
#> [214] "decomposition.slen"
#> [215] "decomposition.d12filter"
#> [216] "decomposition.tlen"
#> [217] "diagnostics.qs"
#> [218] "diagnostics.ftest"
#> [219] "diagnostics.qs.on.i"
#> [220] "diagnostics.ftest.on.i"
#> [221] "diagnostics.combined.all.kruskalwallis"
#> [222] "diagnostics.combined.all.stable"
#> [223] "diagnostics.combined.all.evolutive"
#> [224] "diagnostics.combined.all.summary"
#> [225] "diagnostics.combined.all.stable.ssm"
#> [226] "diagnostics.combined.all.stable.ssr"
#> [227] "diagnostics.combined.all.stable.ssq"
#> [228] "diagnostics.combined.all.evolutive.ssm"
#> [229] "diagnostics.combined.all.evolutive.ssr"
#> [230] "diagnostics.combined.all.evolutive.ssq"
#> [231] "diagnostics.combined.end.kruskalwallis"
#> [232] "diagnostics.combined.end.stable"
#> [233] "diagnostics.combined.end.evolutive"
#> [234] "diagnostics.combined.end.summary"
#> [235] "diagnostics.combined.end.stable.ssm"
#> [236] "diagnostics.combined.end.stable.ssr"
#> [237] "diagnostics.combined.end.stable.ssq"
#> [238] "diagnostics.combined.end.evolutive.ssm"
#> [239] "diagnostics.combined.end.evolutive.ssr"
#> [240] "diagnostics.combined.end.evolutive.ssq"
#> [241] "diagnostics.combined.residual.all.kruskalwallis"
#> [242] "diagnostics.combined.residual.all.stable"
#> [243] "diagnostics.combined.residual.all.evolutive"
#> [244] "diagnostics.combined.residual.all.summary"
#> [245] "diagnostics.combined.residual.all.stable.ssm"
#> [246] "diagnostics.combined.residual.all.stable.ssr"
#> [247] "diagnostics.combined.residual.all.stable.ssq"
#> [248] "diagnostics.combined.residual.all.evolutive.ssm"
#> [249] "diagnostics.combined.residual.all.evolutive.ssr"
#> [250] "diagnostics.combined.residual.all.evolutive.ssq"
#> [251] "diagnostics.combined.residual.end.kruskalwallis"
#> [252] "diagnostics.combined.residual.end.stable"
#> [253] "diagnostics.combined.residual.end.evolutive"
#> [254] "diagnostics.combined.residual.end.summary"
#> [255] "diagnostics.combined.residual.end.stable.ssm"
#> [256] "diagnostics.combined.residual.end.stable.ssr"
#> [257] "diagnostics.combined.residual.end.stable.ssq"
#> [258] "diagnostics.combined.residual.end.evolutive.ssm"
#> [259] "diagnostics.combined.residual.end.evolutive.ssr"
#> [260] "diagnostics.combined.residual.end.evolutive.ssq"
#> [261] "diagnostics.residual.all"
#> [262] "diagnostics.residual.end"
#> [263] "diagnostics.residualtd"
#> [264] "diagnostics.residualtd.on.i"
#> [265] "diagnostics.variancedecomposition"
#> [266] "diagnostics.logstat"
#> [267] "diagnostics.levelstat"
#> [268] "diagnostics.fcast-insample-mean"
#> [269] "diagnostics.fcast-outsample-mean"
#> [270] "diagnostics.fcast-outsample-variance"
#> [271] "diagnostics.seas-lin-f"
#> [272] "diagnostics.seas-lin-qs"
#> [273] "diagnostics.seas-lin-kw"
#> [274] "diagnostics.seas-lin-friedman"
#> [275] "diagnostics.seas-lin-periodogram"
#> [276] "diagnostics.seas-lin-spectralpeaks"
#> [277] "diagnostics.seas-si-combined"
#> [278] "diagnostics.seas-si-evolutive"
#> [279] "diagnostics.seas-si-stable"
#> [280] "diagnostics.seas-res-f"
#> [281] "diagnostics.seas-res-qs"
#> [282] "diagnostics.seas-res-kw"
#> [283] "diagnostics.seas-res-friedman"
#> [284] "diagnostics.seas-res-periodogram"
#> [285] "diagnostics.seas-res-spectralpeaks"
#> [286] "diagnostics.seas-res-combined"
#> [287] "diagnostics.seas-res-combined3"
#> [288] "diagnostics.seas-res-evolutive"
#> [289] "diagnostics.seas-res-stable"
#> [290] "diagnostics.seas-i-f"
#> [291] "diagnostics.seas-i-qs"
#> [292] "diagnostics.seas-i-kw"
#> [293] "diagnostics.seas-i-periodogram"
#> [294] "diagnostics.seas-i-spectralpeaks"
#> [295] "diagnostics.seas-i-combined"
#> [296] "diagnostics.seas-i-combined3"
#> [297] "diagnostics.seas-i-evolutive"
#> [298] "diagnostics.seas-i-stable"
#> [299] "diagnostics.seas-sa-f"
#> [300] "diagnostics.seas-sa-qs"
#> [301] "diagnostics.seas-sa-kw"
#> [302] "diagnostics.seas-sa-friedman"
#> [303] "diagnostics.seas-sa-periodogram"
#> [304] "diagnostics.seas-sa-spectralpeaks"
#> [305] "diagnostics.seas-sa-combined"
#> [306] "diagnostics.seas-sa-combined3"
#> [307] "diagnostics.seas-sa-evolutive"
#> [308] "diagnostics.seas-sa-stable"
#> [309] "diagnostics.seas-sa-ac1"
#> [310] "diagnostics.td-sa-all"
#> [311] "diagnostics.td-sa-last"
#> [312] "diagnostics.td-i-all"
#> [313] "diagnostics.td-i-last"
#> [314] "diagnostics.td-res-all"
#> [315] "diagnostics.td-res-last"
#> [316] "diagnostics.ic-ratio-henderson"
#> [317] "diagnostics.ic-ratio"
#> [318] "diagnostics.msr-global"
#> [319] "diagnostics.msr(*)"
#> [320] "coherence.annualtotals.value"
#> [321] "coherence.annualtotals"
#> [322] "coherence.definition.value"
#> [323] "coherence.definition"
#> [324] "residuals.normality.value"
#> [325] "residuals.normality"
#> [326] "residuals.independence.value"
#> [327] "residuals.independence"
#> [328] "residuals.tdpeaks.value"
#> [329] "residuals.tdpeaks"
#> [330] "residuals.seaspeaks.value"
#> [331] "residuals.seaspeaks"
#> [332] "benchmarking.original"
#> [333] "benchmarking.target"
#> [334] "benchmarking.result"
get_indicators(mysa, "decomposition.b2", "decomposition.d10")
#> $decomposition.b2
#> Jan Feb Mar Apr May Jun Jul
#> 1990 80.81217
#> 1991 79.80106 79.70994 79.67580 79.59134 79.50538 79.47901 79.42114
#> 1992 79.12460 79.05572 78.94483 78.69321 78.52768 78.38786 78.14774
#> 1993 75.90577 75.64151 75.38622 75.15483 74.74513 74.45864 74.50543
#> 1994 75.78817 76.01356 76.27707 76.69293 77.25007 77.93911 78.53318
#> 1995 80.46376 80.67467 80.82205 80.94985 81.04038 81.03817 80.87189
#> 1996 80.71720 80.80987 80.93185 81.01703 81.04874 80.99240 80.97044
#> 1997 82.96634 83.42150 83.91180 84.52530 85.21059 85.84273 86.53911
#> 1998 89.39197 89.70959 89.94590 90.14744 90.35497 90.56634 90.65483
#> 1999 91.68494 91.84151 92.09455 92.46733 92.76597 93.15447 93.70126
#> 2000 96.43072 96.77119 97.04041 97.33407 97.77341 98.14357 98.32554
#> 2001 99.49568 99.71697 99.88142 99.86773 99.71457 99.31793 98.96634
#> 2002 98.11773 97.99744 97.90913 97.83300 97.71788 97.56235 97.40864
#> 2003 96.26634 96.01733 95.82430 95.81697 95.82725 95.85939 95.92661
#> 2004 97.40987 97.59240 97.86924 98.10607 98.12473 98.26210 98.63489
#> 2005 98.82567 98.67189 98.68540 98.59709 98.57507 98.75994 98.77485
#> 2006 99.24709 99.47884 99.58455 99.73318 99.97788 99.99650 99.92606
#> 2007 100.78735 101.13780 101.22309 101.30106 101.48123 101.48876 101.52467
#> 2008 101.17953 100.86024 100.56640 100.09960 99.70514 99.63583 99.32425
#> 2009 95.49335 95.48172 95.65128 95.68191 95.61647 95.36118 95.27884
#> 2010 98.03811 98.34052 98.55189 98.78301 98.91497 99.23265 99.88777
#> 2011 101.50396 101.62936 101.71370 101.83372 102.03670 102.20491 102.15315
#> 2012 101.29141 101.36111 101.28960 101.00371 100.68692 100.27556 99.78270
#> 2013 99.09590 98.91728 98.72897 98.74868 98.78772 98.76135 98.80765
#> 2014 98.58201 98.52467 98.57331 98.55348 98.45543 98.46257 98.51728
#> 2015 98.87015 98.98360 99.24907 99.41728 99.69981 99.95701 100.14134
#> 2016 100.65091 100.54538 100.46192 100.36723 100.26883 100.35471 100.52474
#> 2017 101.28777 101.54868 101.72105 102.10719 102.71022 103.07884 103.15007
#> 2018 103.75302 103.99515 104.01376 103.97923 103.92191 103.80443 103.84451
#> 2019 104.62090 104.58395 104.62481 104.75701 104.63355 104.37385 104.16181
#> 2020 103.61043 103.77713 103.86739 103.67700 103.59975 103.58422 103.49902
#> 2021 102.87236 102.61649 102.44318 102.40254 102.35877 102.37415
#> Aug Sep Oct Nov Dec
#> 1990 80.72092 80.57481 80.37761 79.95447 79.80642
#> 1991 79.31258 79.17659 79.18260 79.42274 79.39140
#> 1992 77.80223 77.33856 76.83957 76.47209 76.16257
#> 1993 74.56176 74.62884 74.77621 74.99568 75.39038
#> 1994 79.03902 79.55030 79.99809 80.21773 80.27290
#> 1995 80.70906 80.64774 80.59556 80.52877 80.60726
#> 1996 81.08645 81.34207 81.73254 82.18911 82.58830
#> 1997 87.21901 87.75070 88.14540 88.57983 88.99930
#> 1998 90.67625 90.75523 90.90207 91.06376 91.38340
#> 1999 94.23108 94.80794 95.34893 95.89637 96.22958
#> 2000 98.59103 98.98077 99.24663 99.19134 99.24705
#> 2001 98.80008 98.65814 98.56511 98.34614 98.17309
#> 2002 97.29076 97.09378 96.97175 96.93077 96.61330
#> 2003 95.98611 96.04220 96.12541 96.41405 96.96983
#> 2004 98.84553 98.79465 98.75869 98.88318 98.96955
#> 2005 98.70568 98.83866 98.96561 98.96356 99.06040
#> 2006 100.07171 100.30161 100.44247 100.47050 100.49705
#> 2007 101.68903 101.68403 101.72731 101.78487 101.53185
#> 2008 98.65558 97.88575 97.03870 96.39804 95.94243
#> 2009 95.46692 95.86673 96.41774 97.00860 97.56574
#> 2010 100.61910 101.23618 101.61689 101.67808 101.51868
#> 2011 101.85923 101.55484 101.40598 101.23693 101.18941
#> 2012 99.51601 99.38632 99.23495 99.17431 99.16793
#> 2013 98.88560 98.90112 98.91659 98.92561 98.75814
#> 2014 98.49302 98.49469 98.55189 98.58717 98.78581
#> 2015 100.27470 100.30268 100.30939 100.54974 100.73075
#> 2016 100.60414 100.77100 100.92295 100.96673 101.06774
#> 2017 103.21238 103.41643 103.57812 103.45284 103.43355
#> 2018 104.09076 104.15886 104.24499 104.67431 104.77626
#> 2019 103.94075 103.79517 103.56296 103.28758 103.40020
#> 2020 103.45236 103.39365 103.38137 103.32283 103.11388
#> 2021
#>
#> $decomposition.d10
#> Jan Feb Mar Apr May
#> 1990 -3.23112424 -2.45358625 6.92606765 0.46855094 -2.53648128
#> 1991 -3.18607624 -2.56877244 6.76211515 0.48073025 -2.43731681
#> 1992 -2.96230026 -2.81860766 6.50479190 0.50513443 -2.44011384
#> 1993 -2.87063337 -3.12899915 6.34172006 0.56849659 -2.62588295
#> 1994 -2.90970212 -3.39113948 6.26254717 0.65764640 -2.95333714
#> 1995 -3.15354010 -3.54121591 6.35424853 0.70143710 -3.24373983
#> 1996 -3.34181747 -3.66292833 6.55920597 0.65038775 -3.44649460
#> 1997 -3.50678240 -3.81445820 6.94945266 0.53539013 -3.53576744
#> 1998 -3.71883351 -3.93407836 7.54825524 0.34440535 -3.56603122
#> 1999 -3.81010166 -3.95497735 8.28627204 0.04759366 -3.63050145
#> 2000 -3.88282400 -3.88906935 9.10645871 -0.06727057 -3.93623910
#> 2001 -3.92507755 -3.71650232 9.76574512 0.03272906 -4.33189628
#> 2002 -3.91951955 -3.57720406 10.07055976 0.37495154 -4.52547101
#> 2003 -3.72159176 -3.59697554 10.01360691 0.67061526 -4.32561681
#> 2004 -3.48856885 -3.74155605 9.77497323 0.85922176 -3.99056174
#> 2005 -3.27607861 -3.85475066 9.45486880 0.92599515 -3.67421933
#> 2006 -3.14050695 -3.85113453 9.04096804 0.82717345 -3.46594093
#> 2007 -3.15341374 -3.77606532 8.71892996 0.69347864 -3.37908023
#> 2008 -3.18834807 -3.45086967 8.53759913 0.58766908 -3.60423841
#> 2009 -3.17511237 -3.12766081 8.45445778 0.67161637 -4.00750317
#> 2010 -3.04966470 -2.83589556 8.44708199 0.72158415 -4.36870140
#> 2011 -3.01837774 -2.68878555 8.59020442 0.94404638 -4.67678706
#> 2012 -3.09085753 -2.43933782 8.84694402 1.14722039 -5.06210593
#> 2013 -3.19643380 -2.33715168 8.87124254 1.51571104 -5.24700795
#> 2014 -3.27646548 -2.43517696 8.81815223 1.61051043 -4.98222683
#> 2015 -3.41496340 -2.76490101 8.65728424 1.50230186 -4.39258367
#> 2016 -3.45672829 -3.11078319 8.57238852 1.13155806 -3.77217598
#> 2017 -3.50989539 -3.44301963 8.47163668 0.57271598 -3.21746805
#> 2018 -3.59158685 -3.61964964 8.56018364 0.04440789 -2.80790959
#> 2019 -3.80462770 -3.59111017 8.63642758 -0.32962167 -2.63209004
#> 2020 -3.95684375 -3.44658475 8.71390004 -0.40887694 -2.64743506
#> Jun Jul Aug Sep Oct
#> 1990 8.58652688 -0.93318080 -26.88627300 5.84425980 9.51277718
#> 1991 8.78444653 -0.96321830 -26.88978248 5.80580137 9.40295915
#> 1992 9.10177488 -0.95685315 -26.87859177 5.74926791 9.19709183
#> 1993 9.58461516 -0.89739294 -26.95134964 5.71343361 9.01884480
#> 1994 10.02989689 -0.72683798 -26.99605412 5.74298632 8.94861147
#> 1995 10.43634302 -0.46190103 -27.25086279 5.82222095 9.03999618
#> 1996 10.73543827 -0.16813261 -27.64165508 5.99403027 9.25566980
#> 1997 10.99323923 0.05291816 -28.13124082 6.10042512 9.50919029
#> 1998 11.09694914 0.22726160 -28.50144380 6.16198789 9.73674073
#> 1999 11.18144533 0.42391323 -28.81976252 6.21380367 9.84430721
#> 2000 11.21797537 0.62328083 -29.09341341 6.38240916 9.99685294
#> 2001 11.36879282 0.74289141 -29.40394895 6.71124769 10.09258545
#> 2002 11.60278864 0.60684880 -29.67420830 7.16980029 10.07521124
#> 2003 11.96015452 0.30360152 -30.00881683 7.69771451 9.86011980
#> 2004 12.31852464 0.09391455 -30.31807523 8.02628768 9.67637687
#> 2005 12.52327924 0.09885612 -30.51238953 8.15681336 9.36344639
#> 2006 12.33958047 0.31153876 -30.20478335 8.06899292 9.05477057
#> 2007 11.88124011 0.60529198 -29.43838637 7.90025983 8.63244476
#> 2008 11.15557250 1.06197675 -28.40162182 7.62353784 8.35573587
#> 2009 10.38873789 1.56844873 -27.26111264 7.44010250 7.86078958
#> 2010 9.78187334 2.00841221 -26.20880904 7.27532429 7.50998794
#> 2011 9.33578933 2.39261457 -25.31053420 7.15696114 7.18826481
#> 2012 9.13588277 2.72058362 -24.63099553 6.91117326 7.20147554
#> 2013 8.96813476 2.91687978 -24.08100452 6.71982618 7.09666821
#> 2014 8.87528633 2.72180065 -23.74022571 6.47653745 7.31380776
#> 2015 8.80293789 2.44110955 -23.51700294 6.18755382 7.53213155
#> 2016 8.83655120 2.15132750 -23.48623552 5.88676109 8.01056701
#> 2017 8.93946680 2.18514995 -23.34438622 5.62725179 8.32254026
#> 2018 9.09029550 2.32669134 -23.23570602 5.45119622 8.74335446
#> 2019 9.27156738 2.67473456 -23.03712953 5.35076837 8.94170126
#> 2020 9.41303027 2.92492541 -22.88952482 5.40065806 9.07499614
#> Nov Dec
#> 1990 3.27525681 1.47198330
#> 1991 3.15895332 1.71980899
#> 1992 3.01106153 2.16973476
#> 1993 2.82218126 2.63980962
#> 1994 2.55444586 2.96552928
#> 1995 2.35284825 3.01697689
#> 1996 2.19656043 2.85046082
#> 1997 2.27065604 2.51098356
#> 1998 2.35882014 1.97624777
#> 1999 2.50690433 1.30097501
#> 2000 2.51666198 0.48630618
#> 2001 2.42153335 -0.29313541
#> 2002 2.20230841 -0.88637417
#> 2003 2.06488215 -1.20658494
#> 2004 2.01191290 -1.37471507
#> 2005 2.18210642 -1.31799891
#> 2006 2.56173475 -1.37520844
#> 2007 2.91907983 -1.56835084
#> 2008 3.09774192 -1.88197812
#> 2009 3.05421329 -2.12864166
#> 2010 2.79143000 -2.39700685
#> 2011 2.35016391 -2.67559624
#> 2012 1.89569400 -2.89923014
#> 2013 1.64129678 -2.89157726
#> 2014 1.74059501 -2.80060355
#> 2015 2.05495041 -2.75281805
#> 2016 2.44475876 -2.84265268
#> 2017 2.74794776 -3.25879500
#> 2018 2.87928835 -3.86713780
#> 2019 2.82444428 -4.53979302
#> 2020 2.63661191 -5.03889824
#>
# To convert the Java object to an R object
jSA2R(mysa)
#> RegARIMA
#> y = regression model + arima (2, 1, 1, 0, 1, 1)
#> Log-transformation: no
#> Coefficients:
#> Estimate Std. Error
#> Phi(1) 0.0003269 0.108
#> Phi(2) 0.1688192 0.074
#> Theta(1) -0.5485606 0.102
#> BTheta(1) -0.6660849 0.042
#>
#> Estimate Std. Error
#> Monday 0.55932 0.228
#> Tuesday 0.88221 0.228
#> Wednesday 1.03996 0.229
#> Thursday 0.04943 0.229
#> Friday 0.91132 0.230
#> Saturday -1.57769 0.228
#> Leap year 2.15403 0.705
#> Easter [1] -2.37950 0.454
#> TC (4-2020) -35.59245 2.173
#> AO (3-2020) -20.89026 2.180
#> AO (5-2011) 13.49850 1.857
#> LS (11-2008) -12.54901 1.636
#>
#>
#> Residual standard error: 2.218 on 342 degrees of freedom
#> Log likelihood = -799.1, aic = 1632 aicc = 1634, bic(corrected for length) = 1.855
#>
#>
#>
#> Decomposition
#> Monitoring and Quality Assessment Statistics:
#> M stats
#> M(1) 0.163
#> M(2) 0.089
#> M(3) 1.181
#> M(4) 0.558
#> M(5) 1.020
#> M(6) 0.090
#> M(7) 0.083
#> M(8) 0.244
#> M(9) 0.062
#> M(10) 0.272
#> M(11) 0.256
#> Q 0.368
#> Q-M2 0.402
#>
#> Final filters:
#> Seasonal filter: 3x5
#> Trend filter: 13 terms Henderson moving average
#>
#>
#> Final
#> Last observed values
#> y sa t s i
#> Jan 2020 101.0 102.95613 102.9586 -1.95613209 -0.002494203
#> Feb 2020 100.1 103.50876 102.9592 -3.40875640 0.549602816
#> Mar 2020 91.8 82.87617 103.1664 8.92382800 -20.290271773
#> Apr 2020 66.7 66.65243 103.5971 0.04756625 -36.944710027
#> May 2020 73.7 78.87836 104.0393 -5.17835604 -25.160905985
#> Jun 2020 98.2 87.34544 104.3804 10.85456021 -17.034985133
#> Jul 2020 97.4 92.47436 104.5319 4.92563707 -12.057551871
#> Aug 2020 71.7 97.47245 104.3751 -25.77244698 -6.902636199
#> Sep 2020 104.7 97.37717 103.9182 7.32282919 -6.541070626
#> Oct 2020 106.7 98.24194 103.3047 8.45805540 -5.062719500
#> Nov 2020 101.6 100.26862 102.7746 1.33138152 -2.506014899
#> Dec 2020 96.6 99.66730 102.5133 -3.06729670 -2.845961796
#>
#> Forecasts:
#> y_f sa_f t_f s_f i_f
#> Jan 2021 94.53021 101.0902 102.4794 -6.56002888 -1.3891608
#> Feb 2021 97.90024 101.7395 102.5246 -3.83928384 -0.7850772
#> Mar 2021 114.09983 102.3065 102.5087 11.79328397 -0.2021598
#> Apr 2021 102.16781 102.2220 102.3759 -0.05422341 -0.1538967
#> May 2021 96.01612 101.5450 102.2100 -5.52888123 -0.6650098
#> Jun 2021 112.76658 101.3438 102.0725 11.42275939 -0.7286526
#> Jul 2021 104.13805 101.6681 102.0297 2.46989932 -0.3615193
#> Aug 2021 79.13003 102.3617 102.1360 -23.23171595 0.2257112
#> Sep 2021 109.06438 102.4772 102.3249 6.58713572 0.1523168
#> Oct 2021 108.64207 102.1329 102.5185 6.50921416 -0.3856588
#> Nov 2021 106.46022 102.5908 102.6996 3.86943752 -0.1088338
#> Dec 2021 99.79901 103.0831 102.8580 -3.28410831 0.2251086
#>
#>
#> Diagnostics
#> Relative contribution of the components to the stationary
#> portion of the variance in the original series,
#> after the removal of the long term trend
#> Trend computed by Hodrick-Prescott filter (cycle length = 8.0 years)
#> Component
#> Cycle 2.251
#> Seasonal 59.750
#> Irregular 1.067
#> TD & Hol. 2.610
#> Others 33.718
#> Total 99.395
#>
#> Combined test in the entire series
#> Non parametric tests for stable seasonality
#> P.value
#> Kruskall-Wallis test 0.000
#> Test for the presence of seasonality assuming stability 0.000
#> Evolutive seasonality test 0.034
#>
#> Identifiable seasonality present
#>
#> Residual seasonality tests
#> P.value
#> qs test on sa 0.985
#> qs test on i 0.865
#> f-test on sa (seasonal dummies) 0.958
#> f-test on i (seasonal dummies) 0.893
#> Residual seasonality (entire series) 0.876
#> Residual seasonality (last 3 years) 0.906
#> f-test on sa (td) 0.987
#> f-test on i (td) 0.993
#>
#>
#> Additional output variables