pub struct FunctionOnFunctionRegression;Expand description
Function-on-function regression.
Model: y_i(t) = integral x_i(s) * beta(s,t) ds + epsilon_i(t)
The bivariate coefficient beta(s,t) is expanded in a tensor product basis: beta(s,t) = sum_{j,k} B_{jk} * phi_j(s) * psi_k(t)
This is solved via penalized least squares on the vectorized coefficients.
Implementations§
Source§impl FunctionOnFunctionRegression
impl FunctionOnFunctionRegression
Sourcepub fn fit(
predictor_data: &FunctionalData,
response_data: &FunctionalData,
predictor_config: &FunctionalConfig,
response_config: &FunctionalConfig,
) -> StatsResult<FoFResult>
pub fn fit( predictor_data: &FunctionalData, response_data: &FunctionalData, predictor_config: &FunctionalConfig, response_config: &FunctionalConfig, ) -> StatsResult<FoFResult>
Fit a function-on-function regression model.
§Arguments
predictor_data- Functional predictor data (n curves)response_data- Functional response data (n curves, possibly different grid)predictor_config- Configuration for predictor basisresponse_config- Configuration for response basis
§Returns
A FoFResult containing the bivariate coefficient surface, fitted curves, etc.
§Errors
Returns an error if dimensions mismatch or the linear system fails.
Sourcepub fn predict(
result: &FoFResult,
new_data: &FunctionalData,
) -> StatsResult<Vec<Vec<f64>>>
pub fn predict( result: &FoFResult, new_data: &FunctionalData, ) -> StatsResult<Vec<Vec<f64>>>
Auto Trait Implementations§
impl Freeze for FunctionOnFunctionRegression
impl RefUnwindSafe for FunctionOnFunctionRegression
impl Send for FunctionOnFunctionRegression
impl Sync for FunctionOnFunctionRegression
impl Unpin for FunctionOnFunctionRegression
impl UnsafeUnpin for FunctionOnFunctionRegression
impl UnwindSafe for FunctionOnFunctionRegression
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