View source: R/add_modelling_features.R
add_modelling_features | R Documentation |
This function adds three main groups of features to the data. It is used
internally in fit_single_contact_model()
and predict_contacts_1y()
.
It requires columns named age_to
and age_from
. The three types of
features it adds are described below:
Population distribution of contact ages from the function
add_population_age_to()
, which requires a column called "age_to"
representing the age of the person who had contact. It creates a column
called pop_age_to
. add_population_age_to()
takes an extra argument
for population, which defaults to get_polymod_population()
, but needs
to be a conmat_population
object, which specifies the age
and
population
characteristics, or a data frame with columns,
lower.age.limit
, and population
.
School work participation, which is from the function
add_school_work_participation()
. This requires columns age_to
and
age_from
, but will operate on any column starting with age
and adds
columns: school_probability
, work_probability
,
school_year_probability
, and school_weighted_pop_fraction
.
Offset is added on to the data using add_offset()
. This requires
variables school_weighted_pop_fraction
(from
add_school_work_participation()
) and pop_age_to
(from
add_school_work_participation()
). It adds two columns,
log_contactable_population_school
, and log_contactable_population
.
add_modelling_features(
contact_data,
school_demographics = NULL,
work_demographics = NULL,
population = get_polymod_population()
)
contact_data |
contact data with columns |
school_demographics |
(optional) defaults to census average proportion
at school. You can provide a dataset with columns, "age" (numeric), and
"school_fraction" (0-1), if you would like to specify these
details. See |
work_demographics |
(optional) defaults to census average proportion
employed. You can provide a dataset with columns, "age" (numeric), and
"work_fraction", if you would like to specify these details. See
|
population |
the |
data frame with 11 extra columns - the contents of contact_data
,
plus: pop_age_to, school_fraction_age_from, work_fraction_age_from,
school_fraction_age_to, work_fraction_age_to, school_probability,
work_probability, school_year_probability, school_weighted_pop_fraction,
log_contactable_population_school, and log_contactable_population.
age_min <- 10
age_max <- 15
all_ages <- age_min:age_max
library(tidyr)
example_df <- expand_grid(
age_from = all_ages,
age_to = all_ages,
)
add_modelling_features(example_df)
add_modelling_features(
example_df,
school_demographics = conmat_original_school_demographics,
work_demographics = conmat_original_work_demographics
)
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