Take a single simulation time step
do_step(
state,
params,
ratemat,
dt = 1,
do_hazard = TRUE,
stoch_proc = FALSE,
do_exponential = FALSE,
testwt_scale = "N"
)named vector of states
named vector of parameters
transition matrix
time step (days)
use hazard calculation?
stochastic process error?
prevent outflow of susceptibles, to create a pure-exponential process?
how to scale testing weights? "none"=use original weights as specified; "N" = multiply by (pop size)/(sum(wts*state[u_pop])); "sum_u" = multiply by (sum(state[u_pop])/(sum(wts*state[u_pop])))
Other classic_macpan:
add_d_log(),
add_updated_vaxrate(),
aggregate_agecats(),
calibrate_comb(),
calibrate(),
check_age_cat_compatibility(),
check_contact_rate_setting(),
col_multiply(),
condense_age(),
condense_params_vax(),
condense_state(),
condense_vax(),
dev_is_tikz(),
expand_params_age(),
expand_params_desc_age(),
expand_params_desc_variant(),
expand_params_desc_vax(),
expand_params_mistry(),
expand_params_variant(),
expand_params_vax(),
expand_state_age(),
expand_state_vax(),
expand_stateval_testing(),
fix_pars(),
fix_stored(),
forecast_ensemble(),
forecast_sim(),
getData(),
get_GI_moments(),
get_Gbar(),
get_R0(),
get_doses_per_day(),
get_evec(),
get_kernel_moments(),
get_opt_pars(),
get_r(),
invlink_trans(),
make_betavec(),
make_beta(),
make_jac(),
make_ratemat(),
make_state(),
make_test_wtsvec(),
make_vaxrate(),
mk_Nvec(),
mk_agecats(),
mk_contact_rate_setting(),
mk_mistry_Nvec(),
mk_pmat(),
mk_vaxcats(),
mle_fun(),
non_expanded_states,
rExp(),
read_params(),
repair_names_age(),
restore(),
run_sim_ageify(),
run_sim_break(),
run_sim_loglin(),
run_sim_mobility(),
run_sim_range(),
run_sim(),
show_ratemat(),
testify(),
texify(),
trans_state_vars(),
update_contact_rate_setting(),
update_foi(),
update_params_mistry(),
vis_model(),
write_params()
params1 <- read_params("ICU1.csv")
state1 <- make_state(params=params1)
M <- make_ratemat(params=params1, state=state1)
s1A <- do_step(state1,params1, M, stoch_proc=TRUE)