Index

Symbols

(2003) (2006) (2012) (2014) (2015) 12.19

2021, [1] 2022, [1] 2023, [1] 2024, [1] 2025, [1] 2do, [1]

A

a_i, [1], [2], [3], [4] abs_covariate_id_set absolute_covariates, [1], [2], [3], [4], [5] absolute_covariates.py absolute_covariates: absolute_tolerance add, [1] add_log_entry age, [1], [2], [3], [4], [5], [6], [7], [8] age-time age_avg_split age_grid, [1], [2], [3] age_id age_lower, [1] age_upper, [1] al., [1], [2] all, [1], [2], [3], [4] all_covariate_table, [1], [2] all_node.db all_node_database, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16] all_node_db allow_same_job

alpha, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11] an, [1], [2], [3] analysis ancestor ancestor_id ancestor_job_dir another are, [1], [2] arguments asymptotic at, [1] at_cascade, [1], [2], [3], [4], [5], [6] at_cascade.constant_table_list at_cascade.csv at_cascade.version at_cascade_log_dict, [1] averages avg_integrand, [1] avgint, [1], [2], [3], [4], [5], [6] avgint_id, [1] avgint_parent_grid avgint_table, [1]

B

balance_fit balance_sex barendregt bib bibliography biegler bilinear, [1], [2]

binomial, [1] binomial_rate boolean both, [1], [2] bound_random breakup breakup_computation

C

c c_age_id c_shift_avgint c_shift_predict_fit_var c_shift_predict_sample c_split_reference_id c_time_id calculate cascade, [1], [2], [3], [4], [5], [6] cascade_root_node cascading cases check, [1], [2], [3] check_cascade_node check_log checking, [1], [2], [3], [4], [5], [6], [7], [8], [9] checks chi, [1] child, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] child_prior_std_factor child_prior_std_factor_mulcov child_rate.csv, [1], [2], [3], [4], [5], [6] children chu clear clear_shared close closet cole column columns, [1], [2] com_cov_reference compress_interval compression compute, [1] connection, [1], [2], [3] const_value, [1] constant, [1] constraints, [1], [2], [3] continue continue_cascade continue_cascade.py continue_cascade: continue_cascade_xam continuing convert copies copy, [1] copy_other_tbl copy_root_db corresponding, [1] cov_info cov_name cov_reference cov_reference_id

cov_reference_list cov_reference_table, [1] cov_same, [1] covariate.csv, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11] covariate_average covariate_both covariate_id covariate_name, [1] covariate_names, [1] covariate_or_sex covariate_reference, [1] covariate_same covariate_table, [1], [2], [3], [4], [5], [6] covariate_table_in covariate_table_out covariates, [1], [2], [3], [4] coverage create, [1], [2], [3], [4], [5], [6], [7], [8] create_all_node_db create_job_table create_shift_db csv, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14] csv.ancestor_fit csv.binomial csv.break_fit_pred csv.check_table csv.cov_both_xam csv.cov_same_xam csv.covariate_avg csv.covariate_both csv.covariate_same csv.covariate_spline csv.coverage csv.empty_str csv.fit, [1], [2] csv.join_file csv.join_file_xam csv.module csv.population csv.pre_one_job csv.pre_one_process csv.pre_parallel csv.pre_user csv.predict csv.prevalence2iota csv.read_table csv.root_node_sex csv.set_truth csv.shock_cov csv.sim_fit_pred csv.simulate, [1] csv.simulate_xam csv.table csv.write_table csv_file, [1], [2] cv

D

dage, [1], [2], [3], [4], [5] dage_prior data_id data_in.csv, [1], [2], [3], [4], [5] data_include data_include_table data_sim.csv database, [1], [2], [3], [4], [5], [6], [7], [8], [9] database_dir db2csv, [1] default, [1] demographer density, [1] density_name depth, [1] descendant

descendent_id determine, [1], [2], [3] direction directly, [1] directory, [1], [2], [3] discussion, [1] dismod dismod-at dismod.db, [1] dismod_at, [1] distribution distributions do dst_name dtime, [1] dtime_prior duration, [1]

E

effected effects, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12] empty, [1], [2] empty_avgint_table empty_directory end_child_job_id entry equation errors

estimation, [1] et, [1], [2] eta, [1], [2] example, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35] example_bilinear examples exception exists extract_avgint

F

file, [1], [2], [3] file_name, [1], [2] files, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14] first_fit fit_children fit_database, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] fit_dir, [1], [2], [3], [4], [5], [6] fit_file, [1], [2] fit_goal.csv, [1], [2], [3], [4], [5], [6], [7], [8] fit_goal_set, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15] fit_goal_table, [1] fit_integrand, [1], [2], [3] fit_job_id fit_node, [1] fit_node_id, [1], [2], [3], [4] fit_node_name, [1] fit_node_set fit_one_job fit_one_process fit_or_root fit_or_root_class, [1] fit_parallel

fit_predict.csv, [1] fit_same_as_predict fit_sex fit_split_reference_id, [1] fit_type, [1] fit_type_list, [1], [2], [3] fit_var, [1] fits, [1] fitted fitting, [1], [2], [3], [4], [5] fixed, [1] flaxman float float_precision, [1], [2] format freeze, [1], [2] freeze_type, [1] from, [1], [2], [3], [4], [5], [6], [7], [8] from_none frozen function, [1] functions

G

gamma, [1] generation get, [1], [2], [3], [4] get_cov_info get_database_dir get_fit_children get_fit_integrand get_freeze_dict

get_parent_node get_table get_var_id git global glossary, [1] goal greenland grid, [1], [2], [3], [4], [5], [6], [7]

H

haqi, [1], [2], [3]

hold_out hold_out_integrand

I

i_i, [1], [2], [3] i_n if, [1] in, [1], [2], [3], [4], [5], [6] incidence, [1], [2] include income, [1], [2], [3] index, [1] information initialize input, [1], [2], [3], [4], [5] input_node_database install integer

integrand integrand_list integrand_name, [1], [2], [3], [4] integrand_step_size integrands interface interpolation, [1] iota, [1], [2], [3], [4], [5] iota_pos_rho_pos iota_pos_rho_zero iota_zero_rho_pos iota_zero_rho_zero is its

J

job, [1], [2], [3], [4] job_descendent job_id job_name, [1]

job_status_name, [1] job_table, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] jobs join joining

K

key, [1]

keys

L

left_file list

log, [1], [2], [3], [4], [5], [6] logs lower

M

map, [1], [2] map_shared math, [1] max_abs_effect, [1] max_fit, [1], [2], [3] max_fit_option, [1] max_fit_option.py max_fit_option: max_job_depth, [1], [2] max_node_depth max_num_iter_fixed max_number_cpu, [1], [2], [3], [4] maximum, [1] mean, [1], [2] meas_mean meas_noise, [1] meas_std, [1] meas_std_cv meas_std_min meas_value, [1], [2] measurement, [1], [2] measures, [1] memory, [1] message

message_dict message_type minimum_meas_cv mm-dd, [1], [2], [3], [4] module, [1], [2] move move_table mtall mtexcess mtother mtspecific mulcov mulcov.csv, [1], [2], [3], [4], [5], [6] mulcov_freeze, [1] mulcov_freeze.py mulcov_freeze: mulcov_freeze_dict mulcov_freeze_id mulcov_freeze_table, [1], [2] mulcov_id, [1] multiplier multiplier_id multiplier_sim.csv, [1], [2] multiplier_truth multipliers, [1]

N

n_omega_age n_omega_time name, [1], [2] names new_random_effects no, [1] no_effect_iota no_effect_rate.csv, [1], [2] no_effect_rate_truth no_ode no_ode_database no_ode_fit, [1], [2], [3], [4] no_ode_ignore, [1] no_ode_xam no_ode_xam.py no_ode_xam: node.csv, [1], [2], [3], [4], [5], [6], [7], [8]

node_dict node_id, [1], [2], [3] node_name, [1], [2], [3], [4], [5], [6], [7], [8], [9] node_set node_split_id node_split_set, [1] node_split_table, [1] node_table, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] noise notation, [1], [2] notes, [1], [2], [3], [4], [5] nslist, [1] nslist_pair nu null_row number, [1], [2], [3], [4] number_cpu_inuse number_sample, [1]

O

ode, [1] ode_integrand ode_iota_omega ode_method ode_step_size, [1], [2] omega, [1], [2], [3], [4], [5], [6], [7], [8] omega_age_grid omega_age_grid_id omega_all, [1] omega_all_id, [1] omega_all_value omega_constraint omega_data omega_grid, [1], [2] omega_index omega_index_id omega_time_grid omega_time_grid_id omega_truth on one, [1], [2], [3], [4], [5], [6], [7]

one_at_function one_at_function.py one_at_function: optimization option, [1], [2], [3], [4] option_all option_all_dict option_all_id option_all_table, [1], [2] option_fit.csv, [1], [2], [3], [4], [5], [6], [7], [8] option_fit_out.csv option_name option_predict, [1] option_predict.csv, [1], [2], [3], [4], [5], [6], [7] option_predict_out.csv option_sim.csv, [1], [2] option_sim_out.csv option_value optional other, [1] output, [1], [2], [3], [4], [5], [6]

P

parallel, [1], [2] parent_job_id parent_name parent_node, [1] parent_node_name parent_rate.csv, [1], [2], [3], [4], [5], [6], [7] particular per, [1] perturb_optimization_scale, [1] perturb_optimization_start pini pirnay plot, [1] population, [1] posterior, [1], [2] pre_database predict, [1] predict_integrand.csv, [1], [2], [3], [4], [5], [6], [7] predict_job_dir predict_job_id

predict_job_id_list predict_job_name predict_node_id predicting prediction, [1], [2], [3], [4], [5], [6] predictions predicts prevalence, [1], [2], [3], [4] prevalence2iota prevalence2iota.py prevalence2iota: primary, [1] prior.csv, [1], [2], [3], [4], [5], [6] prior_only priors, [1], [2], [3] process, [1] processes, [1] processing, [1] prototype, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51] purpose, [1], [2], [3], [4], [5], [6], [7]

Q

quasi_fixed

R

r_n, [1], [2], [3] random_depend_sex random_effect random_effect.csv random_seed, [1], [2], [3], [4] rate_name, [1], [2], [3], [4], [5] rate_table rate_true, [1] rate_truth rate_value, [1] rates, [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] reading rectangular, [1], [2] reference, [1], [2] reference_value references refit_split, [1] regions rel_covariate_id_set relationships relative, [1] relative_tolerance, [1] release, [1], [2], [3], [4], [5] release_notes relrisk remission, [1], [2] remission.py

remission: repository rest, [1] result result_dir result_file results rho right_file risk root, [1], [2] root.db root_database, [1], [2], [3], [4], [5], [6], [7], [8], [9] root_fit_database, [1] root_mulcov_prior_constant root_node root_node_id, [1], [2], [3], [4] root_node_name, [1] root_node_sex root_split_reference_id, [1], [2], [3] root_split_reference_name routines row, [1], [2] row_id row_name rows run, [1] run_job_id

S

s_n, [1], [2], [3] sam_predict.csv, [1] same sample, [1], [2] sample_index, [1], [2] sample_method, [1] sample_size samples, [1], [2] seed, [1], [2], [3], [4], [5], [6] set, [1], [2], [3], [4], [5] sex, [1], [2], [3], [4], [5], [6], [7], [8], [9] sex_name2value sexes shared, [1] shared_event shared_job_status_name, [1] shared_lock, [1] shared_memory_prefix, [1] shared_unique, [1] shift_databases shift_name shift_node_id shift_prior_std_factor shift_prior_std_factor_mulcov shifted shock, [1] side, [1] sim_dir, [1], [2], [3], [4], [5], [6] sim_file, [1] simulate, [1] simulate.csv, [1], [2] simulate_id, [1] simulating, [1] simulation, [1]

sincidence skip_start_job skip_this_job smooth smooth_grid smoothings specified, [1], [2] spline, [1] spline_cov spline_dict split, [1] split_covariate split_covariate.py split_covariate: split_covariate_id split_covariate_name split_reference split_reference_id, [1], [2], [3], [4], [5], [6], [7] split_reference_list split_reference_name, [1] split_reference_table, [1], [2], [3], [4], [5] split_reference_value splitting, [1] src_name start start_child_job_id start_job_id, [1] start_job_name, [1], [2], [3] start_node_id start_split_reference_id starting std std_random_effects_rate std_random_effects_truth summary

T

t table_exists table_in table_name, [1], [2] table_name2id table_out tables, [1], [2], [3], [4], [5] tbl_name test, [1] this_job_id time, [1], [2], [3], [4], [5], [6], [7], [8] time_grid, [1], [2], [3] time_id time_lower, [1]

time_upper, [1] to_none tolerance_fixed top_directory trace trace.out trace_file_obj trapezoidal tree, [1] tru_predict.csv true, [1] truth, [1] two, [1] type, [1]

U

upon upper

use user

V

value_prior, [1], [2] values, [1], [2], [3], [4] var var_table

var_type variables version, [1] versions versus

W

wachter warnings weighting which

wish wish_list with, [1], [2], [3], [4], [5] writing

X

x_grid

x_name

Y

y_grid

y_name

Z

z_list

zero_meas_value