Quantile.0.25(R) always equals Quantile.0.75(R)

[robchallen]

library(EpiEstim)
data(Flu2009)
T <- nrow(Flu2009$incidence)
t_start <- seq(2, T-6) # starting at 2 as conditional on the past observations
t_end <- t_start + 6 # adding 6 to get 7-day windows as bounds included in window
res_weekly <- EpiEstim::estimate_R(Flu2009$incidence, 
                         method="parametric_si",
                         config = EpiEstim::make_config(list(
                             t_start = t_start,
                             t_end = t_end,
                             mean_si = 2.6, 
                             std_si = 1.5)))
res_weekly$R

results in :

t_start t_end   Mean(R)     Std(R) Quantile.0.025(R) Quantile.0.05(R) Quantile.0.25(R) Median(R) Quantile.0.75(R)
1        2     8 1.7357977 0.40913143        1.02874370       1.12193325        2.4589724 1.7037612        2.4589724
2        3     9 1.7491678 0.36472669        1.10882231       1.19547993        2.3891206 1.7238839        2.3891206

Other quantiles look OK

[jstockwin]

Hey @robchallen, thanks for filing the issue.

I agree this looks wrong and indeed can see an obvious problem with the code.

Are you able to confirm if #89 solves the problem?

[robchallen]

I did a:

devtools::install_github("annecori/EpiEstim", ref = "fix-broken-quantiles")

I also tried

devtools::install_github("annecori/EpiEstim", ref = github_pull("89"))

and reran:

T <- nrow(Flu2009$incidence)
t_start <- seq(2, T-6) # starting at 2 as conditional on the past observations
t_end <- t_start + 6 # adding 6 to get 7-day windows as bounds included in window
res_weekly <- EpiEstim::estimate_R(Flu2009$incidence, 
                          method="parametric_si",
                          config = EpiEstim::make_config(list(
                              t_start = t_start,
                              t_end = t_end,
                              mean_si = 2.6, 
                              std_si = 1.5)))
glimpse(res_weekly$R)

both time result was as follows & problem persists:

Observations: 25
Variables: 11
$ t_start             <dbl> 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26
$ t_end               <dbl> 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32
$ `Mean(R)`           <dbl> 1.7357977, 1.7491678, 1.5370581, 1.4318389, 1.4227247, 1.6353733, 1.6639845, 1.6161467, 1.4344239, 1.4…
$ `Std(R)`            <dbl> 0.40913143, 0.36472669, 0.30741163, 0.27059213, 0.25150457, 0.25234358, 0.23300443, 0.20692639, 0.1765…
$ `Quantile.0.025(R)` <dbl> 1.02874370, 1.10882231, 0.99470299, 0.95144658, 0.97314263, 1.17863324, 1.23894574, 1.23622420, 1.1093…
$ `Quantile.0.05(R)`  <dbl> 1.12193325, 1.19547993, 1.06869352, 1.01766106, 1.03580815, 1.24358968, 1.30015068, 1.29149686, 1.1568…
$ `Quantile.0.25(R)`  <dbl> 2.4589724, 2.3891206, 2.0751763, 1.9040473, 1.8601072, 2.0713724, 2.0648767, 1.9708944, 1.7366694, 1.6…
$ `Median(R)`         <dbl> 1.7037612, 1.7238839, 1.5166133, 1.4148298, 1.4079324, 1.6224126, 1.6531215, 1.6073240, 1.4271858, 1.4…
$ `Quantile.0.75(R)`  <dbl> 2.4589724, 2.3891206, 2.0751763, 1.9040473, 1.8601072, 2.0713724, 2.0648767, 1.9708944, 1.7366694, 1.6…
$ `Quantile.0.95(R)`  <dbl> 2.4589724, 2.3891206, 2.0751763, 1.9040473, 1.8601072, 2.0713724, 2.0648767, 1.9708944, 1.7366694, 1.6…
$ `Quantile.0.975(R)` <dbl> 2.6247813, 2.5331192, 2.1955399, 2.0088487, 1.9563365, 2.1657455, 2.1507413, 2.0461979, 1.8005896, 1.7…

also I notice quantile 0,95 is the same as 0,75 and 0,25. Not sure if that was the case before or not.

[jstockwin]

Hm, my fix should solve those other quantiles too - I did notice they were also wrong.

It could just be some install thing your side, or perhaps my fix doesn't work. I'll try and find time to take a proper look at some point...

[robchallen]

There must have been some caching issue when I retested it. Looking at this now the quantile results are appropriate and all different. I think this is fixed.

[jstockwin]

This fix has been pushed to CRAN, in version 2.2-3.