fix: optional delta for fou estimator

Cargo.toml

@@ -41,6 +41,7 @@ ndrustfft = "0.5.0"
 num-complex = { version = "0.4.6", features = ["rand"] }
 plotly = { version = "0.10.0", features = ["plotly_ndarray"] }
 polars = { version = "0.43.1", features = ["lazy"] }
+prettytable-rs = "0.10.0"
 # pyo3 = { version = "0.22.3", features = ["extension-module", "abi3-py38"] }
 quadrature = "0.1.2"
 rand = "0.8.5"

src/main.rs

@@ -1,21 +1,22 @@
+use prettytable::{format, row, Table};
 use std::error::Error;
 use std::fs::File;
 use std::io::{BufRead, BufReader};
 
+use stochastic_rs::stats::fd::FractalDim;
 use stochastic_rs::stats::fou_estimator::{
   FOUParameterEstimationV1, FOUParameterEstimationV2, FilterType,
 };
-use stochastic_rs::stats::fd::FractalDim;
 
 // Import your estimator modules and types here
 // use your_crate::{FOUParameterEstimationV1, FOUParameterEstimationV2, FilterType};
 
 fn main() -> Result<(), Box<dyn Error>> {
   // File paths
   let paths = vec![
-    "./test/kecskekut_original.txt",
-    "./test/kecskekut_sim.txt",
-    "./test/kecskekut_without_jumps.txt",
+    // "./test/kecskekut_original.txt",
+    // "./test/kecskekut_sim.txt",
+    // "./test/kecskekut_without_jumps.txt",
     "./test/komlos_original.txt",
     "./test/komlos_sim.txt",
     "./test/komlos_without_jumps.txt",
@@ -27,29 +28,51 @@ fn main() -> Result<(), Box<dyn Error>> {
     let data = read_vector_from_file(path)?;
 
     // V1 Estimation
+    let delta = 1.0; // Adjust as necessary
     let mut estimator_v1 =
-      FOUParameterEstimationV1::new(data.clone().into(), FilterType::Daubechies);
+      FOUParameterEstimationV1::new(data.clone().into(), FilterType::Daubechies, Some(delta));
     let hurst = FractalDim::new(data.clone().into());
-    let hurst = hurst.higuchi_fd(10);
-    estimator_v1.set_hurst(2. - hurst);
+    let hurst = hurst.higuchi_fd(12);
+    // estimator_v1.set_hurst(2. - hurst);
     let (hurst_v1, sigma_v1, mu_v1, theta_v1) = estimator_v1.estimate_parameters();
-    println!("V1 - Estimated Parameters for {}:", path);
-    println!("  Hurst exponent: {}", hurst_v1);
-    println!("  Sigma: {}", sigma_v1);
-    println!("  Mu: {}", mu_v1);
-    println!("  Theta: {}", theta_v1);
 
     // V2 Estimation
-    let delta = 1.0 / 256.0; // Adjust as necessary
+    let delta = 1.0; // Adjust as necessary
     let n = data.len();
-    let mut estimator_v2 = FOUParameterEstimationV2::new(data.clone().into(), delta, n);
-    estimator_v2.set_hurst(2. - hurst);
+    let mut estimator_v2 = FOUParameterEstimationV2::new(data.clone().into(), Some(delta), n);
+    // estimator_v2.set_hurst(2. - hurst);
     let (hurst_v2, sigma_v2, mu_v2, theta_v2) = estimator_v2.estimate_parameters();
-    println!("V1 - Estimated Parameters for {}:", path);
-    println!("  Hurst exponent: {}", hurst_v2);
-    println!("  Sigma: {}", sigma_v2);
-    println!("  Mu: {}", mu_v2);
-    println!("  Theta: {}", theta_v2);
+
+    let mut table = Table::new();
+    table.set_format(*format::consts::FORMAT_NO_LINESEP_WITH_TITLE);
+    table.add_row(row![
+      "Version",
+      "Hurst",
+      "Sigma",
+      "Mu",
+      "Theta",
+      "exp(Theta)"
+    ]);
+    table.add_row(row![
+      "V1",
+      format!("{:.4}", hurst_v1),
+      format!("{:.4}", sigma_v1),
+      format!("{:.4}", mu_v1),
+      format!("{:.4}", theta_v1),
+      format!("{:.4}", (-theta_v1).exp())
+    ]);
+    table.add_row(row![
+      "V2",
+      format!("{:.4}", hurst_v2),
+      format!("{:.4}", sigma_v2),
+      format!("{:.4}", mu_v2),
+      format!("{:.4}", theta_v2),
+      format!("{:.4}", (-theta_v2).exp())
+    ]);
+
+    // Táblázat kiíratása
+    println!("\nEstimated Parameters for {}:\n", path);
+    table.printstd();
   }
 
   Ok(())

src/stats/fou_estimator.rs

@@ -10,6 +10,7 @@ use crate::stochastic::{noise::fgn::FGN, Sampling};
 pub struct FOUParameterEstimationV1 {
   pub path: Array1<f64>,
   pub filter_type: FilterType,
+  pub delta: Option<f64>,
   // Estimated parameters
   hurst: Option<f64>,
   sigma: Option<f64>,
@@ -64,7 +65,7 @@ impl FOUParameterEstimationV1 {
     let L = self.L;
 
     let series_length = self.path.len();
-    let delta = 1.0 / series_length as f64;
+    let delta: f64 = self.delta.unwrap_or(1.0 / series_length as f64);
 
     let mut const_filter = 0.0;
 
@@ -174,7 +175,7 @@ impl FOUParameterEstimationV1 {
 #[derive(ImplNew)]
 pub struct FOUParameterEstimationV2 {
   pub path: Array1<f64>,
-  pub delta: f64,
+  pub delta: Option<f64>,
   pub series_length: usize,
   // Estimated parameters
   hurst: Option<f64>,
@@ -230,7 +231,7 @@ impl FOUParameterEstimationV2 {
     let H = self.hurst.unwrap();
     let X = &self.path;
     let N = self.series_length as f64;
-    let delta = self.delta;
+    let delta = self.delta.unwrap_or(1.0 / N);
 
     let numerator: f64 = (0..(self.series_length - 2))
       .map(|i| {
@@ -437,7 +438,7 @@ mod tests {
     let fgn = FGN::new(0.70, 4095, Some(1.0), None);
     let fou = FOU::new(5.0, 2.8, 1.0, 4096, Some(X0), Some(16.0), None, fgn);
     let path = fou.sample();
-    let mut estimator = FOUParameterEstimationV1::new(path, FilterType::Daubechies);
+    let mut estimator = FOUParameterEstimationV1::new(path, FilterType::Daubechies, None);
 
     // Estimate the parameters
     let (estimated_hurst, estimated_sigma, estimated_mu, estimated_theta) =
@@ -459,7 +460,7 @@ mod tests {
     let fgn = FGN::new(0.70, N - 1, Some(1.0), None);
     let fou = FOU::new(5.0, 2.8, 2.0, N, Some(X0), Some(16.0), None, fgn);
     let path = fou.sample();
-    let mut estimator = FOUParameterEstimationV2::new(path, delta, N);
+    let mut estimator = FOUParameterEstimationV2::new(path, Some(delta), N);
 
     // Estimate the parameters
     let (estimated_hurst, estimated_sigma, estimated_mu, estimated_theta) =