-
Notifications
You must be signed in to change notification settings - Fork 6
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #145 from palatej/develop
Improvements of high-frequency
- Loading branch information
Showing
20 changed files
with
1,122 additions
and
414 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
178 changes: 178 additions & 0 deletions
178
...c/main/java/jdplus/highfreq/base/core/extendedairline/LightExtendedAirlineEstimation.java
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,178 @@ | ||
| /* | ||
| * Copyright 2024 JDemetra+. | ||
| * Licensed under the EUPL, Version 1.2 or – as soon they will be approved | ||
| * by the European Commission - subsequent versions of the EUPL (the "Licence"); | ||
| * You may not use this work except in compliance with the Licence. | ||
| * You may obtain a copy of the Licence at: | ||
| * | ||
| * https://joinup.ec.europa.eu/software/page/eupl | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the Licence is distributed on an "AS IS" basis, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the Licence for the specific language governing permissions and | ||
| * limitations under the Licence. | ||
| */ | ||
| package jdplus.highfreq.base.core.extendedairline; | ||
|
|
||
| import java.util.List; | ||
| import jdplus.highfreq.base.api.ExtendedAirline; | ||
| import jdplus.highfreq.base.api.ExtendedAirlineSpec; | ||
| import jdplus.toolkit.base.api.data.DoubleSeq; | ||
| import jdplus.toolkit.base.api.data.DoubleSeqCursor; | ||
| import jdplus.toolkit.base.api.data.ParametersEstimation; | ||
| import jdplus.toolkit.base.api.information.GenericExplorable; | ||
| import jdplus.toolkit.base.api.math.matrices.Matrix; | ||
| import jdplus.toolkit.base.api.processing.ProcessingLog; | ||
| import jdplus.toolkit.base.api.timeseries.regression.MissingValueEstimation; | ||
| import jdplus.toolkit.base.core.arima.ArimaModel; | ||
| import jdplus.toolkit.base.core.data.DataBlock; | ||
| import jdplus.toolkit.base.core.regarima.RegArimaEstimation; | ||
| import jdplus.toolkit.base.core.regarima.RegArimaModel; | ||
| import jdplus.toolkit.base.core.regarima.RegArimaUtility; | ||
| import jdplus.toolkit.base.core.stats.likelihood.ConcentratedLikelihoodWithMissing; | ||
| import jdplus.toolkit.base.core.stats.likelihood.LikelihoodStatistics; | ||
| import jdplus.toolkit.base.core.stats.likelihood.LogLikelihoodFunction; | ||
|
|
||
| /** | ||
| * | ||
| * @author Jean Palate | ||
| */ | ||
| @lombok.Value | ||
| @lombok.Builder(toBuilder = true, builderClassName = "Builder") | ||
| public class LightExtendedAirlineEstimation implements GenericExplorable { | ||
|
|
||
| @lombok.NonNull | ||
| private DoubleSeq y; | ||
| @lombok.NonNull | ||
| private Matrix X; | ||
| private boolean mean; | ||
|
|
||
| @lombok.NonNull | ||
| private ExtendedAirline model; | ||
|
|
||
| /** | ||
| * Regression estimation. The order correspond to the order of the variables | ||
| * Fixed coefficients are not included | ||
| */ | ||
| @lombok.NonNull | ||
| private DoubleSeq coefficients; | ||
| @lombok.NonNull | ||
| private Matrix coefficientsCovariance; | ||
|
|
||
| /** | ||
| * Positions corresponding to the estimation domain | ||
| */ | ||
| @lombok.NonNull | ||
| private MissingValueEstimation[] missing; | ||
| /** | ||
| * Parameters of the stochastic component. Fixed parameters are not included | ||
| */ | ||
| @lombok.NonNull | ||
| private ParametersEstimation parameters; | ||
|
|
||
| private LikelihoodStatistics statistics; | ||
|
|
||
| private DoubleSeq fullResiduals; | ||
|
|
||
| @lombok.Singular | ||
| private List<ProcessingLog.Information> logs; | ||
|
|
||
| public static Builder builder() { | ||
| Builder builder = new Builder(); | ||
| builder.y = DoubleSeq.empty(); | ||
| builder.X = Matrix.empty(); | ||
| builder.coefficients = DoubleSeq.empty(); | ||
| builder.coefficientsCovariance = Matrix.empty(); | ||
| builder.missing = NOMISSING; | ||
| builder.parameters = ParametersEstimation.empty(); | ||
| builder.fullResiduals = DoubleSeq.empty(); | ||
| return builder; | ||
| } | ||
|
|
||
| private static final MissingValueEstimation[] NOMISSING = new MissingValueEstimation[0]; | ||
|
|
||
| public static LightExtendedAirlineEstimation of(RegArimaEstimation<ArimaModel> estimation, ExtendedAirlineSpec spec) { | ||
| Builder builder = builder(); | ||
| RegArimaModel<ArimaModel> regarima = estimation.getModel(); | ||
| ConcentratedLikelihoodWithMissing ll = estimation.getConcentratedLikelihood(); | ||
| LogLikelihoodFunction.Point<RegArimaModel<ArimaModel>, ConcentratedLikelihoodWithMissing> max = estimation.getMax(); | ||
| int free = spec.freeParametersCount(); | ||
| int df = ll.degreesOfFreedom() - free; | ||
| double vscale = ll.ssq() / df; | ||
| builder.y(regarima.getY()) | ||
| .X(regarima.variables()) | ||
| .mean(regarima.isMean()) | ||
| .model(ExtendedAirline.of(spec.withFreeParameters(max.getParameters()))) | ||
| .coefficients(ll.coefficients()) | ||
| .coefficientsCovariance(ll.covariance(free, true)); | ||
| ParametersEstimation pestim = new ParametersEstimation(max.getParameters(), max.asymptoticCovariance(), max.getScore(), "Extended airline"); | ||
| builder.parameters(pestim) | ||
| .statistics(estimation.statistics()); | ||
| DoubleSeq fullRes = RegArimaUtility.fullResiduals(regarima, ll); | ||
| builder.fullResiduals(fullRes); | ||
| // complete for missings | ||
| int nmissing = ll.nmissing(); | ||
| if (nmissing > 0) { | ||
| DoubleSeq y = regarima.getY(); | ||
| MissingValueEstimation[] missing = new MissingValueEstimation[nmissing]; | ||
| DoubleSeqCursor cur = ll.missingCorrections().cursor(); | ||
| DoubleSeqCursor vcur = ll.missingUnscaledVariances().cursor(); | ||
| int[] pmissing = regarima.missing(); | ||
| for (int i = 0; i < nmissing; ++i) { | ||
| double m = cur.getAndNext(); | ||
| double v = vcur.getAndNext(); | ||
| missing[i] = new MissingValueEstimation(pmissing[i], y.get(pmissing[i]) - m, Math.sqrt(v * vscale)); | ||
| } | ||
| builder.missing(missing); | ||
| } | ||
| return builder.build(); | ||
| } | ||
|
|
||
| public DoubleSeq originalY() { | ||
| if (y.anyMatch(z -> Double.isNaN(z))) { | ||
| // already contains the missing values | ||
| return y; | ||
| } | ||
| if (missing.length == 0) { | ||
| return y; | ||
| } | ||
| double[] z = y.toArray(); | ||
| for (int i = 0; i < missing.length; ++i) { | ||
| z[missing[i].getPosition()] = Double.NaN; | ||
| } | ||
| return DoubleSeq.of(z); | ||
| } | ||
|
|
||
| public DoubleSeq linearizedData() { | ||
| double[] res = y.toArray(); | ||
|
|
||
| // handle missing values | ||
| if (missing.length > 0) { | ||
| for (int i = 0; i < missing.length; ++i) { | ||
| res[missing[i].getPosition()] = missing[i].getValue(); | ||
| } | ||
| } | ||
| DataBlock e = DataBlock.of(res); | ||
| if (!X.isEmpty()) { | ||
| DoubleSeq regs = regressionEffect(); | ||
| e.sub(regs); | ||
| } | ||
| return e; | ||
| } | ||
|
|
||
| public DoubleSeq regressionEffect() { | ||
|
|
||
| if (coefficients.isEmpty()) { | ||
| return DoubleSeq.empty(); | ||
| } | ||
|
|
||
| DataBlock d = DataBlock.make(y.length()); | ||
| d.setAY(coefficients.get(0), X.column(0)); | ||
| for (int i = 1; i < coefficients.length(); ++i) { | ||
| d.addAY(coefficients.get(i), X.column(i)); | ||
| } | ||
| return d; | ||
| } | ||
|
|
||
| } |
Oops, something went wrong.