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feat: added psudo inv #12

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feat: added psudo inv #12

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20 changes: 12 additions & 8 deletions src/regression.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -32,9 +32,12 @@ pub fn ols<F: Float + Scalar + RealField>(
let at = &x.transpose();
// beta = (A'A)^-1 A'y
let ata = at * x;
let ata_inv = &ata
.try_inverse()
.ok_or_else(|| Error::FailedToInvertMatrix("OLS failed to invert A.T*A".into()))?;

// Try regular inverse first, fallback to pseudo-inverse
let eps = Float::sqrt(F::epsilon());
let ata_inv = &ata.pseudo_inverse(eps)
.map_err(|_| Error::FailedToInvertMatrix("OLS failed to invert A.T*A".into()))?;

let aty = at * y;

// the regression coefficients
Expand Down Expand Up @@ -84,9 +87,10 @@ mod tests {
add_constant(&mut x);
let (beta_hat, t_stats) = super::ols(&y, &x).unwrap();

assert_eq!(beta_hat.get(0).unwrap().to_owned(), 1.0);
assert_eq!(beta_hat.get(1).unwrap().to_owned(), 0.0);

assert_relative_eq!(beta_hat.get(0).unwrap().to_owned(), 1.0, epsilon = 5.0e-5f32);
assert_relative_eq!(beta_hat.get(1).unwrap().to_owned(), 0.0, epsilon = 1.5e-4f32);
let _a = t_stats.get(1).unwrap();
print!("{:?}", _a);
assert!(t_stats.get(1).unwrap().is_nan());
assert!(t_stats.get(0).unwrap().is_infinite());
}
Expand All @@ -98,8 +102,8 @@ mod tests {
add_constant(&mut x);
let (beta_hat, t_stats) = super::ols(&y, &x).unwrap();

assert_eq!(beta_hat.get(1).unwrap().to_owned(), 0.0);
assert_eq!(beta_hat.get(0).unwrap().to_owned(), 1.0);
assert_relative_eq!(beta_hat.get(1).unwrap().to_owned(), 0.0, epsilon = 1.0e-5);
assert_relative_eq!(beta_hat.get(0).unwrap().to_owned(), 1.0, max_relative = 1.0e-5);
assert!(t_stats.get(1).unwrap().is_nan());
assert!(t_stats.get(0).unwrap().is_infinite());
}
Expand Down
6 changes: 3 additions & 3 deletions src/tools/dickeyfuller.rs
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Expand Up @@ -33,10 +33,10 @@ use crate::Error;
/// `unit_root::prelude::distrib::dickeyfuller::get_critical_value`.
///
/// - If $t_{stat} < \mathrm{t_{\mathrm{crit}}(\alpha)}$ then reject $H_0$ at
/// $alpha$ significance level - and thus conclude that the series is stationary.
/// $alpha$ significance level - and thus conclude that the series is stationary.
/// - If $t_{stat} > \mathrm{t_{\mathrm{crit}}(\alpha)}$ then fail to reject $H_0$ at
/// $alpha$ significance level - and thus conclude we cannot reject the hypothesis that
/// the series is not stationary.
/// $alpha$ significance level - and thus conclude we cannot reject the hypothesis that
/// the series is not stationary.
///
/// # Examples:
///
Expand Down
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