Interface for infectious disease modelling using brms.

Interface for infectious disease modelling using brms.

idbrm(data, formula, family, priors, custom_stancode, dry = FALSE, ...)

Arguments

data	A data frame as prepared for modelling using prepare with a class associated with the model prepared for.
formula	A formula as defined using id_formula or as supported by brms::brm.
family	A observation model family as defined in brms.
priors	A list of priors as defined using brms or id_priors. Defaults to the the id_priors defined for the model class being fit.
custom_stancode	A list of stanvars used to define custom stancode in brms. By default uses the code designed for the model class being fit (as specified using id_stancode).
dry	Logical, defaults to TRUE. For testing purposes should just the stan code be output with not fitting done.
...	Additional arguments to pass to brms::brm.

Author

Sam Abbott

Examples

# \donttest{
# define some example data
library(data.table)
dt <- data.table(
   region = "France", cases = seq(10, 500, by = 10),
   date = seq(as.Date("2020-10-01"), by = "days", length.out = 50)
   )
dt[, deaths := as.integer(shift(cases, 5) * 0.1)]
#>     region cases       date deaths
#>  1: France    10 2020-10-01     NA
#>  2: France    20 2020-10-02     NA
#>  3: France    30 2020-10-03     NA
#>  4: France    40 2020-10-04     NA
#>  5: France    50 2020-10-05     NA
#>  6: France    60 2020-10-06      1
#>  7: France    70 2020-10-07      2
#>  8: France    80 2020-10-08      3
#>  9: France    90 2020-10-09      4
#> 10: France   100 2020-10-10      5
#> 11: France   110 2020-10-11      6
#> 12: France   120 2020-10-12      7
#> 13: France   130 2020-10-13      8
#> 14: France   140 2020-10-14      9
#> 15: France   150 2020-10-15     10
#> 16: France   160 2020-10-16     11
#> 17: France   170 2020-10-17     12
#> 18: France   180 2020-10-18     13
#> 19: France   190 2020-10-19     14
#> 20: France   200 2020-10-20     15
#> 21: France   210 2020-10-21     16
#> 22: France   220 2020-10-22     17
#> 23: France   230 2020-10-23     18
#> 24: France   240 2020-10-24     19
#> 25: France   250 2020-10-25     20
#> 26: France   260 2020-10-26     21
#> 27: France   270 2020-10-27     22
#> 28: France   280 2020-10-28     23
#> 29: France   290 2020-10-29     24
#> 30: France   300 2020-10-30     25
#> 31: France   310 2020-10-31     26
#> 32: France   320 2020-11-01     27
#> 33: France   330 2020-11-02     28
#> 34: France   340 2020-11-03     29
#> 35: France   350 2020-11-04     30
#> 36: France   360 2020-11-05     31
#> 37: France   370 2020-11-06     32
#> 38: France   380 2020-11-07     33
#> 39: France   390 2020-11-08     34
#> 40: France   400 2020-11-09     35
#> 41: France   410 2020-11-10     36
#> 42: France   420 2020-11-11     37
#> 43: France   430 2020-11-12     38
#> 44: France   440 2020-11-13     39
#> 45: France   450 2020-11-14     40
#> 46: France   460 2020-11-15     41
#> 47: France   470 2020-11-16     42
#> 48: France   480 2020-11-17     43
#> 49: France   490 2020-11-18     44
#> 50: France   500 2020-11-19     45
#>     region cases       date deaths
dt[is.na(deaths), deaths := 0]
#>     region cases       date deaths
#>  1: France    10 2020-10-01      0
#>  2: France    20 2020-10-02      0
#>  3: France    30 2020-10-03      0
#>  4: France    40 2020-10-04      0
#>  5: France    50 2020-10-05      0
#>  6: France    60 2020-10-06      1
#>  7: France    70 2020-10-07      2
#>  8: France    80 2020-10-08      3
#>  9: France    90 2020-10-09      4
#> 10: France   100 2020-10-10      5
#> 11: France   110 2020-10-11      6
#> 12: France   120 2020-10-12      7
#> 13: France   130 2020-10-13      8
#> 14: France   140 2020-10-14      9
#> 15: France   150 2020-10-15     10
#> 16: France   160 2020-10-16     11
#> 17: France   170 2020-10-17     12
#> 18: France   180 2020-10-18     13
#> 19: France   190 2020-10-19     14
#> 20: France   200 2020-10-20     15
#> 21: France   210 2020-10-21     16
#> 22: France   220 2020-10-22     17
#> 23: France   230 2020-10-23     18
#> 24: France   240 2020-10-24     19
#> 25: France   250 2020-10-25     20
#> 26: France   260 2020-10-26     21
#> 27: France   270 2020-10-27     22
#> 28: France   280 2020-10-28     23
#> 29: France   290 2020-10-29     24
#> 30: France   300 2020-10-30     25
#> 31: France   310 2020-10-31     26
#> 32: France   320 2020-11-01     27
#> 33: France   330 2020-11-02     28
#> 34: France   340 2020-11-03     29
#> 35: France   350 2020-11-04     30
#> 36: France   360 2020-11-05     31
#> 37: France   370 2020-11-06     32
#> 38: France   380 2020-11-07     33
#> 39: France   390 2020-11-08     34
#> 40: France   400 2020-11-09     35
#> 41: France   410 2020-11-10     36
#> 42: France   420 2020-11-11     37
#> 43: France   430 2020-11-12     38
#> 44: France   440 2020-11-13     39
#> 45: France   450 2020-11-14     40
#> 46: France   460 2020-11-15     41
#> 47: France   470 2020-11-16     42
#> 48: France   480 2020-11-17     43
#> 49: France   490 2020-11-18     44
#> 50: France   500 2020-11-19     45
#>     region cases       date deaths

dt <- prepare(
  dt, model = "convolution", location = "region",
  primary = "cases", secondary = "deaths",
  )

# fit the convolution model using a Poisson observation model
fit <- idbrm(data = dt, family = poisson(identity = "link"))
#> Error in poisson(identity = "link") unused argument (identity = "link")
# }