Functions
real	delay_snap_lpmf (array[] int dummy, int start, int end, array[] int obs, array[] int sl, array[] int csl, array[] int nsl, array[] int cnsl, array[] int obs_lookup, array[] vector imp_obs, array[] int sg, array[] int st, array[,] int rdlurd, vector srdlh, matrix refp_lh, array[] int dpmfs, int ref_p, int rep_h, int ref_as_p, array[] real phi, int model_obs, vector refnp_lh, int ref_np, array[] int sdmax, array[] int csdmax)

real	delay_group_lpmf (array[] int groups, int start, int end, array[] int obs, array[] int sl, array[] int csl, array[] int nsl, array[] int cnsl, array[] int obs_lookup, array[] vector imp_obs, int t, array[] int sg, array[,] int ts, array[] int st, array[,] int rdlurd, vector srdlh, matrix refp_lh, array[] int dpmfs, int ref_p, int rep_h, int ref_as_p, array[] real phi, int model_obs, int model_miss, int miss_obs, array[] int missing_reference, array[,] int obs_by_report, vector miss_ref_lprop, array[] int sdmax, array[] int csdmax, array[] int miss_st, array[] int miss_cst, vector refnp_lh, int ref_np)

Function Documentation

◆ delay_group_lpmf()

real delay_group_lpmf	(	array[]int	groups,
		int	start,
		int	end,
		array[]int	obs,
		array[]int	sl,
		array[]int	csl,
		array[]int	nsl,
		array[]int	cnsl,
		array[]int	obs_lookup,
		array[]vector	imp_obs,
		int	t,
		array[]int	sg,
		array int	ts[,],
		array[]int	st,
		array int	rdlurd[,],
		vector	srdlh,
		matrix	refp_lh,
		array[]int	dpmfs,
		int	ref_p,
		int	rep_h,
		int	ref_as_p,
		array[]real	phi,
		int	model_obs,
		int	model_miss,
		int	miss_obs,
		array[]int	missing_reference,
		array int	obs_by_report[,],
		vector	miss_ref_lprop,
		array[]int	sdmax,
		array[]int	csdmax,
		array[]int	miss_st,
		array[]int	miss_cst,
		vector	refnp_lh,
		int	ref_np
	)

Log probability mass function for delayed group data

Computes the log probability mass for a range of time indexes in delayed group data. It manages data filtering, allocation for expected log observations, and handles missing data if applicable.

Parameters

start	Start index for the range of interest.
end	End index for the range of interest.
obs	Array of observed data, stored as a flat vector.
sl	Array of start index for each observation period.
csl	Array of cumulative start indexes.
nsl	Array of next start indexes, indicating the start of the next period.
cnsl	Array of cumulative next start indexes.
obs_lookup	Array of indexes linking observed data to modeled expectations.
imp_obs	Array of imputed observed data, organized by group and time.
sg	Array indicating group index for each observation.
st	Array indicating time index for each observation.
rdlurd	Array indicating reporting dates lookup reference data.
srdlh	Vector of standardized reporting date log hazards.
refp_lh	Matrix of reference date logit hazards.
dpmfs	Array of indices for accessing reference date effects in `refp_lh`.
ref_p	Binary flag for reference date effects presence.
rep_h	Binary flag for reporting hazard effects presence.
ref_as_p	Binary flag indicating if reference date input should be treated as probability.
phi	Array of dispersion parameters for negative binomial distribution.
model_obs	Binary flag indicating if a negative binomial model is used.
refnp_lh	Vector of non-parametric reference log hazards.
ref_np	Binary flag for non-parametric reference effects presence.
sdmax	Array of maximum start dates for each period.
csdmax	Array of cumulative start dates.
groups	Array of group identifiers.
t	Integer representing the current time index.
groups	Array of group identifiers.
ts	Array of snapshot indices by time and group.
model_miss	Binary flag indicating if missing observations should be modeled (0 = no, 1 = yes).
miss_obs	Number of observations with missing reference dates.
missing_reference	Array of observations reported without a reference date (by reporting time).
obs_by_report	Array of observation indices by reference date for entries in missing_reference.
miss_ref_lprop	Vector of log probabilities for missing reference dates.
miss_st	Array of start indices for observations by group in missing_reference.
miss_cst	Array of cumulative start indices for observations by group in missing_reference.

Returns: Log probability mass of the observations for the specified range.

Note

This function performs the following operations:

Determines the relevant range for observed and missing data.
Filters and allocates expected log observations, handling missing data.
Computes expected log observations using expected_obs_from_snaps.
Applies the observation error model using obs_lpmf.
Additionally, handles missing data using apply_missing_reference_effects and log_expected_by_report if model_miss is 1.

Dependencies:

filt_obs_indexes
expected_obs_from_snaps
obs_lpmf
allocate_observed_obs
apply_missing_reference_effects
log_expected_by_report.

This function is similar to delay_snap_lpmf but is specifically designed for group data and includes additional steps for missing data.

Definition at line 122 of file delay_lpmf.stan.

◆ delay_snap_lpmf()

real delay_snap_lpmf	(	array[]int	dummy,
		int	start,
		int	end,
		array[]int	obs,
		array[]int	sl,
		array[]int	csl,
		array[]int	nsl,
		array[]int	cnsl,
		array[]int	obs_lookup,
		array[]vector	imp_obs,
		array[]int	sg,
		array[]int	st,
		array int	rdlurd[,],
		vector	srdlh,
		matrix	refp_lh,
		array[]int	dpmfs,
		int	ref_p,
		int	rep_h,
		int	ref_as_p,
		array[]real	phi,
		int	model_obs,
		vector	refnp_lh,
		int	ref_np,
		array[]int	sdmax,
		array[]int	csdmax
	)

Log probability mass function for delayed snapshot data

Computes the log probability mass for a range of time indexes in delayed snapshot data. It applies filters to identify relevant observations and calculates the expected log observations based on various inputs.