Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Loading required package: lme4
Loading required package: Matrix
Attaching package: 'lmerTest'
The following object is masked from 'package:lme4':
lmer
The following object is masked from 'package:stats':
step
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats 1.0.0 ✔ readr 2.1.5
✔ ggplot2 3.5.1 ✔ stringr 1.5.1
✔ lubridate 1.9.3 ✔ tibble 3.2.1
✔ purrr 1.0.2 ✔ tidyr 1.3.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(modelr)
library(purrr)
library(emmeans)
Welcome to emmeans.
Caution: You lose important information if you filter this package's results.
See '? untidy'
Attaching package: 'gridExtra'
The following object is masked from 'package:dplyr':
combine
library(writexl)
library(gt)
library(webshot2)
library(broom.mixed)
library(lubridate)
# A tibble: 19,890 × 19
feature sow time_group_60 datetime hour ttf mean_value
<fct> <fct> <fct> <dttm> <fct> <dbl> <dbl>
1 Area 1 1 2025-04-01 09:13:30 9 -17.9 58046.
2 Area 1 2 2025-04-01 10:00:01 10 -17.0 56895.
3 Area 1 3 2025-04-01 11:00:00 11 -16.0 58349.
4 Area 1 4 2025-04-01 12:00:00 12 -15.0 50050.
5 Area 1 5 2025-04-01 13:00:02 13 -14.0 47858.
6 Area 1 6 2025-04-01 14:00:02 14 -13.0 50943.
7 Area 1 7 2025-04-01 15:00:01 15 -12.0 50301.
8 Area 1 8 2025-04-01 16:00:01 16 -11.0 53684.
9 Area 1 9 2025-04-01 17:00:01 17 -10.0 47713.
10 Area 1 10 2025-04-01 18:00:00 18 -9.03 54449.
# ℹ 19,880 more rows
# ℹ 12 more variables: sd_value <dbl>, var_value <dbl>, n_obs <int>,
# .fitted <dbl>, .fixed <dbl>, .mu <dbl>, .offset <dbl>, .sqrtXwt <dbl>,
# .sqrtrwt <dbl>, .weights <dbl>, .wtres <dbl>, .resid <dbl>
aug_resid <- aug_res_60$.resid[16]
aug_resid
y <- aug_res_60$mean_value[16]
est <- aug_res_60$.fitted[16]
obs_resid <- y-est
obs_resid
df_60_min_vars$fixed$estimate[1]