To extract a quality report from the csv file containing the diagnostics matrix.
Value
a QR_matrix object.
Details
This function generates a quality report from a csv file containing
diagnostics (usually from the file demetra_m.csv).
The demetra_m.csv file can be generated by launching the cruncher
(functions cruncher or
cruncher_and_param) with the default export
parameters, having used the default option csv_layout = "vtable" to
format the output tables of the functions
cruncher_and_param and
create_param_file when creating the parameters
file.
This function returns a QR_matrix object, which is a list of 3
objects:
modalities, adata.framecontaining several indicators and their categorical quality (Good, Uncertain, Bad, Severe).values, adata.framecontaining the same indicators and the values that lead to their quality category (i.e.: p-values, statistics, etc.) as well as additional variables that don't have a modality/quality (series frequency and arima model).score_formulathat will store the formula used to calculate the score (when relevant). Its initial value isNULL.
See also
Other QR_matrix functions:
export_xlsx(),
export_xlsx.QR_matrix(),
export_xlsx.mQR_matrix(),
rbind.QR_matrix(),
sort(),
weighted_score()
Examples
# Path of matrix demetra_m
demetra_path <- file.path(
system.file("extdata", package = "JDCruncheR"),
"WS/ws_ipi/Output/SAProcessing-1",
"demetra_m.csv"
)
# Extract the quality report from the demetra_m file
QR <- extract_QR(demetra_path)
print(QR)
#> The quality report matrix has 13 observations
#> There are 18 indicators in the modalities matrix and 20 indicators in the values matrix
#>
#> The quality report matrix contains the following variables:
#> series qs_residual_sa_on_sa f_residual_sa_on_sa qs_residual_sa_on_i f_residual_sa_on_i f_residual_td_on_sa f_residual_td_on_i residuals_independency residuals_normality residuals_homoskedasticity residuals_skewness residuals_kurtosis oos_mean oos_mse m7 q q_m2 pct_outliers frequency arima_model
#>
#> The variables exclusively found in the values matrix are:
#> frequency arima_model
#>
#> No score was calculated
# Extract the modalities matrix:
QR$modalities
#> series qs_residual_sa_on_sa f_residual_sa_on_sa qs_residual_sa_on_i
#> 1 RF0610 Good Good Good
#> 2 RF0620 Good Good Good
#> 3 RF0811 Good Good Good
#> 4 RF0812 Good Good Good
#> 5 RF0893 Good Good Good
#> 6 RF0899 Good Good Good
#> 7 RF1011 Severe Good Severe
#> 8 RF1012 Severe Good Severe
#> 9 RF1013 Bad Good Uncertain
#> 10 RF1020 Severe Good Severe
#> 11 RF1031 Bad Good Bad
#> 12 RF1032 Good Good Good
#> 13 RF1039 Severe Good Severe
#> f_residual_sa_on_i f_residual_td_on_sa f_residual_td_on_i
#> 1 Good Bad Uncertain
#> 2 Good Good Good
#> 3 Good Severe Bad
#> 4 Good Severe Severe
#> 5 Good Good Good
#> 6 Good Bad Bad
#> 7 Good Severe Severe
#> 8 Good Severe Severe
#> 9 Good Severe Severe
#> 10 Good Severe Severe
#> 11 Good Uncertain Uncertain
#> 12 Good Severe Severe
#> 13 Good Severe Severe
#> residuals_independency residuals_normality residuals_homoskedasticity
#> 1 Good Good Good
#> 2 Good Bad Bad
#> 3 Bad Bad Bad
#> 4 Bad Good Good
#> 5 Uncertain Good Good
#> 6 Bad Good Good
#> 7 Bad Good Good
#> 8 Bad Good Good
#> 9 Bad Bad Bad
#> 10 Bad Uncertain Good
#> 11 Bad Bad Uncertain
#> 12 Bad Good Good
#> 13 Bad Bad Uncertain
#> residuals_skewness residuals_kurtosis oos_mean oos_mse m7 q q_m2
#> 1 Good Good Good Bad Good Good Good
#> 2 Bad Bad Bad Bad Good Good Good
#> 3 Bad Bad Good Uncertain Good Bad Bad
#> 4 Good Good Good Good Good Good Good
#> 5 Good Good Bad Good Good Bad Bad
#> 6 Good Good Bad Good Good Good Good
#> 7 Good Good Good Good Good Bad Bad
#> 8 Good Good Bad Good Good Bad Bad
#> 9 Bad Bad Bad Good Bad Bad Bad
#> 10 Good Good Bad Uncertain Good Good Bad
#> 11 Uncertain Uncertain Uncertain Bad Good Good Good
#> 12 Good Good Bad Good Good Bad Bad
#> 13 Uncertain Uncertain Bad Uncertain Good Good Good
#> pct_outliers
#> 1 Uncertain
#> 2 Bad
#> 3 Good
#> 4 Good
#> 5 Good
#> 6 Good
#> 7 Good
#> 8 Good
#> 9 Good
#> 10 Good
#> 11 Uncertain
#> 12 Good
#> 13 Good
# Or:
QR[["modalities"]]
#> series qs_residual_sa_on_sa f_residual_sa_on_sa qs_residual_sa_on_i
#> 1 RF0610 Good Good Good
#> 2 RF0620 Good Good Good
#> 3 RF0811 Good Good Good
#> 4 RF0812 Good Good Good
#> 5 RF0893 Good Good Good
#> 6 RF0899 Good Good Good
#> 7 RF1011 Severe Good Severe
#> 8 RF1012 Severe Good Severe
#> 9 RF1013 Bad Good Uncertain
#> 10 RF1020 Severe Good Severe
#> 11 RF1031 Bad Good Bad
#> 12 RF1032 Good Good Good
#> 13 RF1039 Severe Good Severe
#> f_residual_sa_on_i f_residual_td_on_sa f_residual_td_on_i
#> 1 Good Bad Uncertain
#> 2 Good Good Good
#> 3 Good Severe Bad
#> 4 Good Severe Severe
#> 5 Good Good Good
#> 6 Good Bad Bad
#> 7 Good Severe Severe
#> 8 Good Severe Severe
#> 9 Good Severe Severe
#> 10 Good Severe Severe
#> 11 Good Uncertain Uncertain
#> 12 Good Severe Severe
#> 13 Good Severe Severe
#> residuals_independency residuals_normality residuals_homoskedasticity
#> 1 Good Good Good
#> 2 Good Bad Bad
#> 3 Bad Bad Bad
#> 4 Bad Good Good
#> 5 Uncertain Good Good
#> 6 Bad Good Good
#> 7 Bad Good Good
#> 8 Bad Good Good
#> 9 Bad Bad Bad
#> 10 Bad Uncertain Good
#> 11 Bad Bad Uncertain
#> 12 Bad Good Good
#> 13 Bad Bad Uncertain
#> residuals_skewness residuals_kurtosis oos_mean oos_mse m7 q q_m2
#> 1 Good Good Good Bad Good Good Good
#> 2 Bad Bad Bad Bad Good Good Good
#> 3 Bad Bad Good Uncertain Good Bad Bad
#> 4 Good Good Good Good Good Good Good
#> 5 Good Good Bad Good Good Bad Bad
#> 6 Good Good Bad Good Good Good Good
#> 7 Good Good Good Good Good Bad Bad
#> 8 Good Good Bad Good Good Bad Bad
#> 9 Bad Bad Bad Good Bad Bad Bad
#> 10 Good Good Bad Uncertain Good Good Bad
#> 11 Uncertain Uncertain Uncertain Bad Good Good Good
#> 12 Good Good Bad Good Good Bad Bad
#> 13 Uncertain Uncertain Bad Uncertain Good Good Good
#> pct_outliers
#> 1 Uncertain
#> 2 Bad
#> 3 Good
#> 4 Good
#> 5 Good
#> 6 Good
#> 7 Good
#> 8 Good
#> 9 Good
#> 10 Good
#> 11 Uncertain
#> 12 Good
#> 13 Good