# ECG data
data("twins")
head(twins)
#> # A tibble: 6 x 23
#> # Groups:   patid, hour [6]
#>   patid   age   bmi race  smoking hptn  dm    chf   prevchd med_beta_blocke…
#>   <dbl> <dbl> <dbl> <fct> <fct>   <fct> <fct> <fct> <fct>   <fct>           
#> 1     1    49  27.4 0     1       1     0     0     0       0               
#> 2     1    49  27.4 0     1       1     0     0     0       0               
#> 3     1    49  27.4 0     1       1     0     0     0       0               
#> 4     1    49  27.4 0     1       1     0     0     0       0               
#> 5     1    49  27.4 0     1       1     0     0     0       0               
#> 6     1    49  27.4 0     1       1     0     0     0       0               
#> # … with 13 more variables: med_antidepr <fct>, beck_total <dbl>,
#> #   sad_bin <fct>, sad_cat <fct>, PETdiff_2 <fct>, dyxtime <dttm>, date <date>,
#> #   hour <dbl>, rDYX <dbl>, sDYX <dbl>, HR <dbl>, CP <dbl>, zip <chr>

# Outcomes data
data("mims")
head(mims)
#> # A tibble: 6 x 11
#>   patid first_visit_dat… ldka       mi_date_1  mi_date_2  mi_date_3  CHF_DATE_1
#>   <dbl> <date>           <date>     <date>     <date>     <date>     <date>    
#> 1     1 2012-07-27       2017-10-23 NA         NA         NA         NA        
#> 2     2 2012-08-15       2017-07-17 NA         NA         NA         NA        
#> 3     3 2012-08-27       2012-08-29 NA         NA         NA         NA        
#> 4     4 2012-08-29       2017-07-10 NA         NA         NA         NA        
#> 5     5 2012-09-04       2017-07-20 NA         NA         NA         NA        
#> 6     6 2012-09-21       2017-07-10 NA         NA         NA         NA        
#> # … with 4 more variables: CHF_DATE_2 <date>, CHF_DATE_3 <date>,
#> #   DEATH_CV_YN <dbl>, RDR_ISCHEMIA_M_YN_bl <dbl>

# VCG data
data("geh")
head(geh)
#> # A tibble: 6 x 70
#>      pid hhp_id   age sex   age_cat systolic_bp_fir… systolic_bp_sec…
#>    <dbl>  <dbl> <dbl> <fct> <fct>              <dbl>            <dbl>
#> 1 200481 220946    42 0     0                    162              165
#> 2 200489 224643    62 1     1                    133              128
#> 3 200495 224845    84 0     2                    100               99
#> 4 200052 222917    65 0     2                    139              141
#> 5 200517 220638    64 1     1                    166              163
#> 6 200623 224862    57 0     1                    151              144
#> # … with 63 more variables: systolic_bp_third <dbl>, diastolic_bp_first <dbl>,
#> #   diastolic_bp_second <dbl>, diastolic_bp_third <dbl>,
#> #   pulse_rate_first <dbl>, pulse_rate_second <dbl>, height_cm <dbl>,
#> #   weight_kg <dbl>, waist_cm <dbl>, dia_trt_allopdrug <hvn_lbll>,
#> #   hbp_trt_allopdrug <hvn_lbll>, hyp_trt_allopdrug <hvn_lbll>,
#> #   lab_hba1c <dbl>, lab_fasting_bg <dbl>, lab_fasting_insulin <dbl>,
#> #   lab_tchol <dbl>, lab_ldlchol <dbl>, lab_hdlchol <dbl>, lab_triglyc <dbl>,
#> #   lab_ser_urea <dbl>, lab_ser_creatinine <dbl>, lab_urin_malbumin <dbl>,
#> #   pd_heart <hvn_lbll>, bmi <dbl>, bmi_cat <dbl>, obese <fct>,
#> #   obese_asian <fct>, sbp_mean <dbl>, dbp_mean <dbl>, pulse_mean <dbl>,
#> #   htn <fct>, cad <fct>, drugs_dm <fct>, dm <fct>, dm_lab <fct>,
#> #   dm_control <fct>, dm_pre <fct>, homa <dbl>, high_waist <fct>,
#> #   high_tchol <fct>, high_ldl <fct>, low_hdl <fct>, high_triglyc <fct>,
#> #   met_syn_num <dbl>, met_syn <fct>, pr_interval <dbl>, p_duration <dbl>,
#> #   p_amp <dbl>, qrs_duration <dbl>, qt_interval <dbl>, cornell_voltage <fct>,
#> #   nhanes_score <dbl>, svg_mag <dbl>, az_svg <dbl>, az_svg_m <dbl>,
#> #   el_svg <dbl>, el_svg_m <dbl>, qrs_tang <dbl>, auc_vm_qt <dbl>, wvg <dbl>,
#> #   log_svg <dbl>, log_auc_qt <dbl>, log_wvg <dbl>

m <- cosinor(rDYX ~ hour, twins, tau = c(24, 12))
summary(m)
#> Individual Cosinor Model 
#> ------------------------------------------
#> Call: 
#> cosinor(formula = rDYX ~ M + A1 * cos(2*pi*hour/24 + phi1) + A2 * cos(2*pi*hour/12 + phi2) 
#> 
#> Period(s): 24, 12 
#> 
#> Residuals: 
#>     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
#> -3.00770 -0.52024 -0.03247  0.00000  0.48753  4.88552 
#> 
#> Coefficients: 
#>         Estimate  Std. Error
#> mesor  2.8586510 0.006062639
#> amp1   0.2964114 0.008702368
#> amp2   0.1302012 0.008542526
#> phi1  -2.6542757 0.028911445
#> phi2  -3.6636921 0.065235427
ggcosinor(m)
#> This is a harmonic multiple-component cosinor object. The orthophase, bathyphase, and global amplitude were calculated.
#> Warning in regularize.values(x, y, ties, missing(ties)): collapsing to unique
#> 'x' values
#> `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'

head(augment(m))
#> # A tibble: 6 x 8
#>       y     t     x1        x2        z1        z2 .fitted .resid
#>   <dbl> <dbl>  <dbl>     <dbl>     <dbl>     <dbl>   <dbl>  <dbl>
#> 1  2.63     8 -0.500 -5.00e- 1  8.66e- 1 -8.66e- 1    3.22 -0.592
#> 2  2.42     9 -0.707 -1.84e-16  7.07e- 1 -1.00e+ 0    3.21 -0.787
#> 3  1.81    10 -0.866  5.00e- 1  5.00e- 1 -8.66e- 1    3.15 -1.34 
#> 4  2.01    11 -0.966  8.66e- 1  2.59e- 1 -5.00e- 1    3.08 -1.07 
#> 5  1.63    12 -1      1.00e+ 0  1.22e-16 -2.45e-16    3.01 -1.38 
#> 6  1.95    13 -0.966  8.66e- 1 -2.59e- 1  5.00e- 1    2.95 -0.996