TheilSen trend statistics

[raffaele-morelli]

Question

Hi,

I am working on data with missing months:

• 2018-09
• 2018-01
• 2018-12
• 2019-01
  as shown in TheilSen plot.

Looking at MKresults$data[[2]] we see a table with two lines, one referring to 2019-06-27 and the other to 2018-11-08.

default	p.stars	date	conc	a	b	upper.a	upper.b	lower.a	lower.b	p	slope	intercept	intercept.lower	intercept.upper	lower	upper	slope.percent	lower.percent	upper.percent
default	**	2019-06-27	16.11156	55.92575	-0.0023145	28.85148	-0.0007367	86.20022	-0.0040051	0.0033389	-0.8447789	55.92575	86.20022	28.85148	-1.461859	-0.2688846	-4.957488	-7.730342	-1.632108
default	NA	2018-11-08	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	-4.957488	-7.730342	-1.632108

Why two lines with all NaN except for slope.percent lower.percent upper.percent ?

Data around november 2018 follows

obs	date	meteo	v_norm
11	2018-08-14	12.686618	-1.686618
7	2018-08-26	10.537685	-3.537685
10	2018-10-29	12.546518	-2.546518
14	2018-10-30	12.760691	1.239309
55	2019-02-28	18.897843	36.102157
34	2019-03-01	13.481293	20.518707
42	2019-03-02	16.437182	25.562818
35	2019-03-03	16.784798	18.215202
14	2019-03-04	12.479097	1.520903
6	2019-03-05	10.300994	-4.300993
4	2019-03-06	8.724356	-4.724356
7	2019-03-07	9.382038	-2.382038
6	2019-03-08	10.920722	-4.920722
5	2019-03-09	12.816521	-7.816521

Regards

[mooibroekd]

Reprex to confirm:

library(openair) 
mary <- importAURN(site = "my1", year = c(seq(2000, 2009, 1), seq(2011, 2019, 1)))
result <- TheilSen(mary, pollutant = "no2")
#> Taking bootstrap samples. Please wait.

result$data[[2]]
#> # A tibble: 2 × 20
#>   default p.stars date        conc     a         b upper.a   upper.b lower.a
#>   <chr>   <chr>   <date>     <dbl> <dbl>     <dbl>   <dbl>     <dbl>   <dbl>
#> 1 default ***     2009-12-06  94.7  137.  -0.00305    118.  -0.00182    158.
#> 2 default <NA>    2010-06-16 NaN    NaN  NaN          NaN  NaN          NaN 
#> # ℹ 11 more variables: lower.b <dbl>, p <dbl>, slope <dbl>, intercept <dbl>,
#> #   intercept.lower <dbl>, intercept.upper <dbl>, lower <dbl>, upper <dbl>,
#> #   slope.percent <dbl>, lower.percent <dbl>, upper.percent <dbl>

^{Created on 2024-08-07 with reprex v2.1.1}

However, you can see that the slope.percent, lower.percent and upper.percent are the same as the initial line. I suspect this is a bug when combining the data output, in the sense that those percentages are added twice. When calculating a single line, I would explicitly target the first results (i.e. result$data[[2]][1,])