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turnbull: Handle situation where EM algorithm yields exact solution

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RunasSudo 2023-10-29 13:53:20 +11:00
parent c87f42a042
commit 993e4ba3e2
Signed by: RunasSudo
GPG Key ID: 7234E476BF21C61A
1 changed files with 8 additions and 2 deletions
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src/turnbull.rs
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@ -311,7 +311,7 @@ fn fit_turnbull_estimator(data: &mut TurnbullData, progress_bar: ProgressBar, ma
// --------
// ICM step
let (p_new, s_new, ll_model_new) = do_icm_step(data, &p, &s, ll_model_after_em);
let (p_new, s_new, ll_model_new) = do_icm_step(data, &p, &s, ll_tolerance, ll_model_after_em);
let ll_change = ll_model_new - ll_model;
let converged = ll_change <= ll_tolerance;
@ -400,7 +400,7 @@ fn do_em_step(data: &TurnbullData, p: &Vec<f64>, s: &Vec<f64>) -> Vec<f64> {
return p_new;
}
fn do_icm_step(data: &TurnbullData, _p: &Vec<f64>, s: &Vec<f64>, ll_model: f64) -> (Vec<f64>, Vec<f64>, f64) {
fn do_icm_step(data: &TurnbullData, p: &Vec<f64>, s: &Vec<f64>, ll_tolerance: f64, ll_model: f64) -> (Vec<f64>, Vec<f64>, f64) {
// Compute Λ, the cumulative hazard
// Since Λ = -inf when survival is 1, and Λ = inf when survival is 0, these are omitted
// The entry at lambda[j] corresponds to the survival immediately before time point j + 1
@ -477,6 +477,12 @@ fn do_icm_step(data: &TurnbullData, _p: &Vec<f64>, s: &Vec<f64>, ll_model: f64)
return (p_new, s_new, ll_model_new);
}
if ll_model - ll_model_new < ll_tolerance {
// LL decreased but by less than ll_tolerance
// This might happen because the EM algorithm already obtained the exact solution
return (p.clone(), s.clone(), ll_model);
}
step_size_exponent += 1;
if step_size_exponent > 10 {