tests/testthat/_snaps/partial-prediction.md

In njtierney/conmat: Builds Contact Matrices using GAMs and Population Data

Partial prediction functions work for a single model setting

Code
  partials_home
Output
  # A tibble: 58,806 x 22
     age_from age_to gam_age_offdiag gam_age_offdiag_2 gam_age_diag_prod
   *    <dbl>  <dbl>           <int>             <dbl>             <int>
   1        1      1               0                 0                 1
   2        1      1               0                 0                 1
   3        1      1               0                 0                 1
   4        1      1               0                 0                 1
   5        1      1               0                 0                 1
   6        1      1               0                 0                 1
   7        2      1               1                 1                 2
   8        2      1               1                 1                 2
   9        2      1               1                 1                 2
  10        2      1               1                 1                 2
  # i 58,796 more rows
  # i 17 more variables: gam_age_diag_sum <int>, gam_age_pmax <int>,
  #   gam_age_pmin <int>, pop_age_to <dbl>, intergenerational <int>,
  #   school_fraction_age_from <dbl>, school_fraction_age_to <dbl>,
  #   school_probability <dbl>, school_year_probability <dbl>,
  #   school_weighted_pop_fraction <dbl>, work_fraction_age_from <dbl>,
  #   work_fraction_age_to <dbl>, work_probability <dbl>, ...

Partial prediction functions work for all model settings

Code
  partials_setting
Output
  # A tibble: 235,224 x 23
     setting age_from age_to gam_age_offdiag gam_age_offdiag_2 gam_age_diag_prod
   * <chr>      <dbl>  <dbl>           <int>             <dbl>             <int>
   1 home           1      1               0                 0                 1
   2 home           1      1               0                 0                 1
   3 home           1      1               0                 0                 1
   4 home           1      1               0                 0                 1
   5 home           1      1               0                 0                 1
   6 home           1      1               0                 0                 1
   7 home           2      1               1                 1                 2
   8 home           2      1               1                 1                 2
   9 home           2      1               1                 1                 2
  10 home           2      1               1                 1                 2
  # i 235,214 more rows
  # i 17 more variables: gam_age_diag_sum <int>, gam_age_pmax <int>,
  #   gam_age_pmin <int>, pop_age_to <dbl>, intergenerational <int>,
  #   school_fraction_age_from <dbl>, school_fraction_age_to <dbl>,
  #   school_probability <dbl>, school_year_probability <dbl>,
  #   school_weighted_pop_fraction <dbl>, work_fraction_age_from <dbl>,
  #   work_fraction_age_to <dbl>, work_probability <dbl>, ...

Partial prediction sum functions work for a single model setting

Code
  partials_summed_home
Output
  # A tibble: 9,801 x 3
     age_from age_to gam_total_term
   *    <dbl>  <dbl>          <dbl>
   1        1      1          1.51 
   2        1      2          1.55 
   3        1      3          1.55 
   4        1      4          1.50 
   5        1      5          1.43 
   6        1      6          1.33 
   7        1      7          1.21 
   8        1      8          1.07 
   9        1      9          0.934
  10        1     10          0.794
  # i 9,791 more rows

Code
  partials_summed_setting
Output
  # A tibble: 39,204 x 4
     setting age_from age_to gam_total_term
   * <chr>      <dbl>  <dbl>          <dbl>
   1 home           1      1          1.51 
   2 home           1      2          1.55 
   3 home           1      3          1.55 
   4 home           1      4          1.50 
   5 home           1      5          1.43 
   6 home           1      6          1.33 
   7 home           1      7          1.21 
   8 home           1      8          1.07 
   9 home           1      9          0.934
  10 home           1     10          0.794
  # i 39,194 more rows

njtierney/conmat documentation built on April 17, 2025, 10:27 p.m.