Functions to provide information for all output objects (series, diagnostics,
parameters) available with x13() function.
Value
x13_dictionary() returns a character vector containing the
names of all output objects (series, diagnostics, parameters) available with
the x13() function, whereas x13_full_dictionary() returns a
data.frame with format and description, for all the output objects.
Details
These functions provide lists of output names (series, diagnostics,
parameters) available with the x13() function. These names can be
used to generate customized outputs with the userdefined option of the
x13() function (see examples).
The x13_full_dictionary function provides additional information on
object format and description.
Examples
# \donttest{
# Visualize the dictionary
print(x13_dictionary())
#> List of possible outputs:
#>
#> - period
#> - span.start
#> - span.end
#> - span.n
#> - span.missing
#> - log
#> - ...
#>
#> For a complete list of all outputs, please call summary()
#> For a detailled summary of all outputs, please use the function `x13_full_dictionary()` or `tramoseats_full_dictionary()`
summary(x13_dictionary())
#> List of possible outputs:
#>
#> - period
#> - span.start
#> - span.end
#> - span.n
#> - span.missing
#> - log
#> - adjust
#> - likelihood.ll
#> - likelihood.adjustedll
#> - likelihood.ssqerr
#> - likelihood.aic
#> - likelihood.bic
#> - likelihood.aicc
#> - likelihood.bicc
#> - likelihood.bic2
#> - likelihood.hannanquinn
#> - likelihood.nparams
#> - likelihood.nobs
#> - likelihood.neffectiveobs
#> - likelihood.df
#> - arima.p
#> - arima.d
#> - arima.q
#> - arima.bp
#> - arima.bd
#> - arima.bq
#> - arima.theta(*)
#> - arima.phi(*)
#> - arima.btheta(*)
#> - arima.bphi(*)
#> - regression.espan.start
#> - regression.espan.end
#> - regression.espan.n
#> - regression.espan.missing
#> - regression.mean
#> - regression.nlp
#> - regression.ntd
#> - regression.leaster
#> - regression.nmh
#> - regression.nout
#> - regression.nao
#> - regression.nls
#> - regression.ntc
#> - regression.nso
#> - regression.nusers
#> - regression.mu
#> - regression.lp
#> - regression.td(*)
#> - regression.td-derived
#> - regression.td-ftest
#> - regression.easter
#> - regression.outlier(*)
#> - regression.user(*)
#> - regression.missing(*)
#> - residuals.res
#> - residuals.tsres
#> - residuals.n
#> - residuals.df
#> - residuals.dfc
#> - residuals.ser
#> - residuals.ser_ml
#> - residuals.type
#> - residuals.mean
#> - residuals.skewness
#> - residuals.kurtosis
#> - residuals.doornikhansen
#> - residuals.lb
#> - residuals.bp
#> - residuals.lb2
#> - residuals.bp2
#> - residuals.seaslb
#> - residuals.seasbp
#> - residuals.nruns
#> - residuals.lruns
#> - residuals.nudruns
#> - residuals.ludruns
#> - regression.ml.parameters
#> - regression.ml.pcovar
#> - regression.ml.pcovar-ml
#> - regression.ml.pcorr
#> - regression.ml.pscore
#> - regression.details.description
#> - regression.details.type
#> - regression.details.coefficients
#> - regression.details.covar
#> - regression.details.covar-ml
#> - y
#> - y_f(?)
#> - y_ef(?)
#> - y_b(?)
#> - y_eb(?)
#> - yc
#> - yc_f(?)
#> - yc_b(?)
#> - ylin
#> - ylin_f(?)
#> - ylin_b(?)
#> - det
#> - det_f(?)
#> - det_b(?)
#> - cal
#> - cal_f(?)
#> - cal_b(?)
#> - ycal
#> - ycal_f(?)
#> - ycal_b(?)
#> - tde
#> - tde_f(?)
#> - tde_b(?)
#> - ee
#> - ee_f(?)
#> - ee_b(?)
#> - omhe
#> - omhe_f(?)
#> - omhe_b(?)
#> - mhe
#> - mhe_f(?)
#> - mhe_b(?)
#> - out
#> - out_f(?)
#> - out_b(?)
#> - reg
#> - reg_f(?)
#> - reg_b(?)
#> - l
#> - l_f(?)
#> - l_b(?)
#> - full_res
#> - mode
#> - seasonal
#> - sa
#> - t
#> - s
#> - i
#> - sa_f
#> - t_f
#> - s_f
#> - i_f
#> - out_t
#> - out_s
#> - out_i
#> - reg_t
#> - reg_s
#> - reg_i
#> - reg_sa
#> - reg_u
#> - reg_y
#> - det_t
#> - det_s
#> - det_i
#> - out_t_f(?)
#> - out_s_f(?)
#> - out_i_f(?)
#> - reg_t_f(?)
#> - reg_s_f(?)
#> - reg_i_f(?)
#> - reg_sa_f(?)
#> - reg_u_f(?)
#> - reg_y_f(?)
#> - det_t_f(?)
#> - det_s_f(?)
#> - det_i_f(?)
#> - out_t_b(?)
#> - out_s_b(?)
#> - out_i_b(?)
#> - reg_t_b(?)
#> - reg_s_b(?)
#> - reg_i_b(?)
#> - reg_sa_b(?)
#> - reg_u_b(?)
#> - reg_y_b(?)
#> - det_t_b(?)
#> - det_s_b(?)
#> - det_i_b(?)
#> - decomposition.y_cmp
#> - decomposition.y_cmp_f
#> - decomposition.y_cmp_b
#> - decomposition.sa_cmp
#> - decomposition.t_cmp
#> - decomposition.s_cmp
#> - decomposition.i_cmp
#> - preadjustment.a1
#> - preadjustment.a1a
#> - preadjustment.a1b
#> - preadjustment.a6
#> - preadjustment.a7
#> - preadjustment.a8
#> - preadjustment.a8t
#> - preadjustment.a8i
#> - preadjustment.a8s
#> - preadjustment.a9
#> - preadjustment.a9
#> - preadjustment.a9cal
#> - preadjustment.a9u
#> - preadjustment.a9sa
#> - preadjustment.a9ser
#> - decomposition.b1
#> - decomposition.b2
#> - decomposition.b3
#> - decomposition.b4
#> - decomposition.b5
#> - decomposition.b6
#> - decomposition.b7
#> - decomposition.b8
#> - decomposition.b9
#> - decomposition.b10
#> - decomposition.b11
#> - decomposition.b13
#> - decomposition.b17
#> - decomposition.b20
#> - decomposition.c1
#> - decomposition.c2
#> - decomposition.c4
#> - decomposition.c5
#> - decomposition.c6
#> - decomposition.c7
#> - decomposition.c9
#> - decomposition.c10
#> - decomposition.c11
#> - decomposition.c13
#> - decomposition.c17
#> - decomposition.c20
#> - decomposition.d1
#> - decomposition.d2
#> - decomposition.d4
#> - decomposition.d5
#> - decomposition.d6
#> - decomposition.d7
#> - decomposition.d8
#> - decomposition.d9
#> - decomposition.d10
#> - decomposition.d11
#> - decomposition.d12
#> - decomposition.d13
#> - decomposition.x11-all
#> - decomposition.icratio
#> - decomposition.trend-filter
#> - decomposition.seasonal-filters
#> - decomposition.d9-global-msr
#> - decomposition.d9-msr
#> - decomposition.d9-msr-table
#> - finals.d11
#> - finals.d12
#> - finals.d13
#> - finals.d16
#> - finals.d18
#> - finals.d11a
#> - finals.d12a
#> - finals.d16a
#> - finals.d18a
#> - finals.d11b
#> - finals.d12b
#> - finals.d16b
#> - finals.d18b
#> - finals.e1
#> - finals.e2
#> - finals.e3
#> - finals.e11
#> - diagnostics.seas-lin-combined
#> - diagnostics.seas-lin-evolutive
#> - diagnostics.seas-lin-stable
#> - diagnostics.seas-si-combined
#> - diagnostics.seas-si-combined3
#> - diagnostics.seas-si-evolutive
#> - diagnostics.seas-si-stable
#> - diagnostics.seas-res-combined
#> - diagnostics.seas-res-combined3
#> - diagnostics.seas-res-evolutive
#> - diagnostics.seas-res-stable
#> - diagnostics.seas-sa-combined
#> - diagnostics.seas-sa-combined3
#> - diagnostics.seas-sa-evolutive
#> - diagnostics.seas-sa-stable
#> - diagnostics.seas-i-combined
#> - diagnostics.seas-i-combined3
#> - diagnostics.seas-i-evolutive
#> - diagnostics.seas-i-stable
#> - diagnostics.seas-lin-qs
#> - diagnostics.seas-lin-f
#> - diagnostics.seas-lin-friedman
#> - diagnostics.seas-lin-kw
#> - diagnostics.seas-lin-periodogram
#> - diagnostics.seas-lin-spectralpeaks
#> - diagnostics.seas-res-qs
#> - diagnostics.seas-res-f
#> - diagnostics.seas-res-friedman
#> - diagnostics.seas-res-kw
#> - diagnostics.seas-res-periodogram
#> - diagnostics.seas-res-spectralpeaks
#> - diagnostics.seas-sa-qs
#> - diagnostics.seas-sa-f
#> - diagnostics.seas-sa-friedman
#> - diagnostics.seas-sa-kw
#> - diagnostics.seas-sa-periodogram
#> - diagnostics.seas-sa-spectralpeaks
#> - diagnostics.seas-i-qs
#> - diagnostics.seas-i-f
#> - diagnostics.seas-i-friedman
#> - diagnostics.seas-i-kw
#> - diagnostics.seas-i-periodogram
#> - diagnostics.seas-i-spectralpeaks
#> - diagnostics.seas-sa-ac1
#> - diagnostics.td-res-all
#> - diagnostics.td-res-last
#> - diagnostics.td-sa-all
#> - diagnostics.td-sa-last
#> - diagnostics.td-i-all
#> - diagnostics.td-i-last
#> - diagnostics.fcast-insample-mean
#> - diagnostics.fcast-outsample-mean
#> - diagnostics.fcast-outsample-variance
#> - m-statistics.m1
#> - m-statistics.m2
#> - m-statistics.m3
#> - m-statistics.m4
#> - m-statistics.m5
#> - m-statistics.m6
#> - m-statistics.m7
#> - m-statistics.m8
#> - m-statistics.m9
#> - m-statistics.m10
#> - m-statistics.m11
#> - m-statistics.q
#> - m-statistics.q-m2
#> - variancedecomposition.cycle
#> - variancedecomposition.seasonality
#> - variancedecomposition.irregular
#> - variancedecomposition.tdh
#> - variancedecomposition.others
#> - variancedecomposition.total
#> - quality.summary
#> - benchmarking.original
#> - benchmarking.target
#> - benchmarking.result
#>
#> For a detailled summary of all outputs, please use the function `x13_full_dictionary()` or `tramoseats_full_dictionary()`
# first 10 lines
head(x13_full_dictionary(), n = 10)
#> name description
#> 1 period period of the series
#> 2 span.start start of the considered (partial) series
#> 3 span.end end of the considered (partial) series
#> 4 span.n number of periods in the considered (partial) series
#> 5 span.missing number of missing values in the considered (partial) s...
#> 6 log log-transformtion
#> ...
#>
#> For a complete list of all outputs, please call summary()
#>
#> For more informations about the type, the java class of the output or additive details, call `View()`.
# For more structured information call `View(x13_full_dictionary())`
# Extract names of output of interest
user_defined_output <- x13_dictionary()[c(65, 95, 135)]
user_defined_output
#> [1] "residuals.kurtosis" "ylin" "sa_f"
# Generate the corresponding output in an estimation
y <- rjd3toolkit::ABS$X0.2.09.10.M
m <- x13(y,"rsa3", userdefined=user_defined_output)
# Retrieve user defined output
tail(m$user_defined$ylin)
#> Mar Apr May Jun Jul Aug
#> 2017 1370.3 1522.6 1452.4 1557.2 1445.5 1303.1
m$user_defined$residuals.kurtosis
#> Value: 3.143851
#> P-Value: 0.5512
m$user_defined$sa_f
#> Jan Feb Mar Apr May Jun Jul Aug
#> 2017
#> 2018 1545.102 1550.995 1544.872 1558.419 1556.812 1546.513 1552.880 1555.686
#> Sep Oct Nov Dec
#> 2017 1559.713 1541.278 1551.031 1550.678
#> 2018
# }