turnbull: Use Illinois method rather than interval bisection for likelihood-ratio confidence intervals

27% speedup
NB: Regula falsi alone without Illinois adjustment was slower than interval bisection
This commit is contained in:
RunasSudo 2023-12-26 19:18:38 +11:00
parent 760e3bbb0e
commit 759c2c4778
Signed by: RunasSudo
GPG Key ID: 7234E476BF21C61A
2 changed files with 41 additions and 14 deletions

View File

@ -14,48 +14,75 @@
// You should have received a copy of the GNU Affero General Public License
// along with this program. If not, see <https://www.gnu.org/licenses/>.
pub struct BisectionRootFinder {
pub struct IllinoisRootFinder {
bound_lower: f64,
bound_upper: f64,
value_lower: f64,
value_upper: f64
value_upper: f64,
last_sign: f64 // Sign of the function at last evaluation (1.0 or -1.0) or 0.0 if first iteration
}
impl BisectionRootFinder {
pub fn new(bound_lower: f64, bound_upper: f64, value_lower: f64, value_upper: f64,) -> BisectionRootFinder {
return BisectionRootFinder {
impl IllinoisRootFinder {
pub fn new(bound_lower: f64, bound_upper: f64, value_lower: f64, value_upper: f64) -> IllinoisRootFinder {
return IllinoisRootFinder {
bound_lower: bound_lower,
bound_upper: bound_upper,
value_lower: value_lower,
value_upper: value_upper
value_upper: value_upper,
last_sign: 0.0
}
}
pub fn update(&mut self, guess: f64, value: f64) {
pub fn update(&mut self, guess: f64, mut value: f64) {
if value > 0.0 {
if self.value_lower > 0.0 || self.value_upper < 0.0 {
self.bound_lower = guess;
self.value_lower = value;
if self.last_sign == 1.0 {
// Illinois adjustment: Halve the y-value of the retained end point (the other end point) when the new y-value has the same sign as the previous one
self.value_upper *= 0.5;
}
} else {
self.bound_upper = guess;
self.value_upper = value;
if self.last_sign == 1.0 {
self.value_lower *= 0.5;
}
}
self.last_sign = 1.0;
} else {
if self.value_lower < 0.0 || self.value_upper > 0.0 {
self.bound_lower = guess;
self.value_lower = value;
if self.last_sign == -1.0 {
self.value_upper *= 0.5;
}
} else {
self.bound_upper = guess;
self.value_upper = value;
if self.last_sign == -1.0 {
self.value_lower *= 0.5;
}
}
self.last_sign = -1.0;
}
}
pub fn next_guess(&self) -> f64 {
return (self.bound_lower + self.bound_upper) / 2.0;
if self.value_lower.is_nan() || self.value_upper.is_nan() {
// Fall back to interval bisection
return (self.bound_lower + self.bound_upper) / 2.0;
} else {
// Regula falsi
return (self.bound_lower * self.value_upper - self.bound_upper * self.value_lower) / (self.value_upper - self.value_lower);
}
}
pub fn precision(&self) -> f64 {
return self.bound_upper - self.bound_lower;
return (self.bound_upper - self.bound_lower).abs();
}
}

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@ -29,7 +29,7 @@ use serde::{Serialize, Deserialize};
use crate::csv::read_csv;
use crate::pava::monotonic_regression_pava;
use crate::root_finding::BisectionRootFinder;
use crate::root_finding::IllinoisRootFinder;
use crate::term::UnconditionalTermLike;
#[derive(Args)]
@ -622,7 +622,7 @@ fn compute_hessian(data: &TurnbullData, p: &Vec<f64>) -> DMatrix<f64> {
fn survival_prob_likelihood_ratio_ci(data: &TurnbullData, progress_bar: ProgressBar, max_iterations: u32, ll_tolerance: f64, ci_precision: f64, p: &Vec<f64>, ll_model: f64, s: &Vec<f64>, oim_se: &Vec<f64>, time_index: usize) -> (f64, f64) {
// Compute lower confidence limit
let mut root_finder = BisectionRootFinder::new(
let mut root_finder = IllinoisRootFinder::new(
0.0, s[time_index],
f64::NAN, -CHI2_1DF_95 // Value of (lr_statistic - CHI2_1DF_95), which we are seeking the roots of
);
@ -660,14 +660,14 @@ fn survival_prob_likelihood_ratio_ci(data: &TurnbullData, progress_bar: Progress
let ci_lower = ci_estimate;
// Compute upper confidence limit
root_finder = BisectionRootFinder::new(
root_finder = IllinoisRootFinder::new(
s[time_index], 1.0,
-CHI2_1DF_95, f64::NAN
-CHI2_1DF_95, f64::NAN // Value of (lr_statistic - CHI2_1DF_95), which we are seeking the roots of
);
ci_estimate = s[time_index] + Z_97_5 * oim_se[time_index - 1];
if ci_estimate > 1.0 {
ci_estimate = root_finder.next_guess();
ci_estimate = root_finder.next_guess(); // Returns interval midpoint in this case
}
let mut iteration = 1;