ssm examples added

jdplus-examples-base/jdplus-examples-base-parent/jdplus-examples-base-core/src/main/java/jdplus/examples/base/core/ssm/BasicStructuralModel.java

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+/*
+ * Click nbfs://nbhost/SystemFileSystem/Templates/Licenses/license-default.txt to change this license
+ * Click nbfs://nbhost/SystemFileSystem/Templates/Classes/Class.java to edit this template
+ */
+package jdplus.examples.base.core.ssm;
+
+import jdplus.sts.base.api.SeasonalModel;
+import jdplus.sts.base.core.SeasonalComponent;
+import jdplus.toolkit.base.api.data.DoubleSeq;
+import jdplus.toolkit.base.core.data.DataBlock;
+import jdplus.toolkit.base.core.data.DataBlockStorage;
+import jdplus.toolkit.base.core.math.functions.IParametersDomain;
+import jdplus.toolkit.base.core.math.functions.ParamValidation;
+import jdplus.toolkit.base.core.math.functions.levmar.LevenbergMarquardtMinimizer;
+import jdplus.toolkit.base.core.math.functions.ssq.ISsqFunction;
+import jdplus.toolkit.base.core.math.functions.ssq.ISsqFunctionPoint;
+import jdplus.toolkit.base.core.ssf.StateComponent;
+import jdplus.toolkit.base.core.ssf.composite.CompositeSsf;
+import jdplus.toolkit.base.core.ssf.dk.DkToolkit;
+import jdplus.toolkit.base.core.ssf.likelihood.DiffuseLikelihood;
+import jdplus.toolkit.base.core.ssf.sts.LocalLinearTrend;
+import jdplus.toolkit.base.core.ssf.sts.Noise;
+import jdplus.toolkit.base.core.ssf.univariate.Ssf;
+import jdplus.toolkit.base.core.ssf.univariate.SsfData;
+import tck.demetra.data.Data;
+
+/**
+ *
+ * @author LEMASSO
+ */
+@lombok.experimental.UtilityClass
+public class BasicStructuralModel {
+     public void main(String[] args){
+
+     SsfData data= new SsfData(Data.US_UNEMPL);
+
+     // Example 1: Fixed parameters
+     StateComponent llt = LocalLinearTrend.stateComponent(1, 1);
+     StateComponent seas = SeasonalComponent.of(SeasonalModel.HarrisonStevens, 4, 1);
+     StateComponent n = Noise.of(1);    
+     CompositeSsf ssf1 = CompositeSsf.builder()
+                .add(llt, LocalLinearTrend.defaultLoading())
+                .add(seas, SeasonalComponent.defaultLoading())
+                .add(n, Noise.defaultLoading())
+                .build();
+     DataBlockStorage rslt1 = DkToolkit.fastSmooth(ssf1, data);   
+     System.out.println("Example 1:");
+     System.out.println(rslt1.item(0));
+     System.out.println(rslt1.item(1));
+     System.out.println(rslt1.item(2));
+     System.out.println(rslt1.item(3));
+     System.out.println(rslt1.item(4));
+     System.out.println(rslt1.item(5));
+     DataBlock Z=DataBlock.make(ssf1.getStateDim());
+     ssf1.measurement().loading().Z(0, Z);
+     System.out.println("Z");
+     System.out.println(Z);
+     System.out.println();
+
+
+     // Example 2: Estimated parameters
+     BSM fn = new BSM(DoubleSeq.of(Data.US_UNEMPL));   
+     ISsqFunctionPoint ssq = fn.ssqEvaluate(DoubleSeq.of(.1,.1,.1));
+     LevenbergMarquardtMinimizer lm = LevenbergMarquardtMinimizer.builder()
+             .functionPrecision(0.001)
+             .maxIter(30)
+             .build();
+     boolean ok = lm.minimize(ssq);
+     BSM_Point result = (BSM_Point) lm.getResult();
+     Ssf ssf2 = result.ssf();
+     DataBlockStorage rslt2 = DkToolkit.fastSmooth(ssf2, data);
+     DoubleSeq p2 = result.getParameters();
+     System.out.println("Example 2:");
+     System.out.println(rslt2.item(0));
+     System.out.println(rslt2.item(1));
+     System.out.println(rslt2.item(2));
+     System.out.println(rslt2.item(3));
+     System.out.println(rslt2.item(4));
+     System.out.println(rslt2.item(5));
+     System.out.println("parameter");
+     System.out.println(p2);
+
+    }
+}    
+
+class BSM_Domain implements IParametersDomain{
+
+    @Override
+    public boolean checkBoundaries(DoubleSeq inparams) {
+        return true;
+    }
+
+    @Override
+    public double epsilon(DoubleSeq inparams, int idx) {
+        return 1e-6;
+    }
+
+    @Override
+    public int getDim() {
+        return 3;
+    }
+
+    @Override
+    public double lbound(int idx) {
+        return Double.NEGATIVE_INFINITY;
+    }
+
+    @Override
+    public double ubound(int idx) {
+        return Double.POSITIVE_INFINITY;
+    }
+
+    @Override
+    public ParamValidation validate(DataBlock ioparams) {
+        return ParamValidation.Valid;
+    }
+}
+
+class BSM implements ISsqFunction{
+
+    private final DoubleSeq data; 
+
+    public BSM(DoubleSeq data){
+        this.data=data;
+    }
+
+    public DoubleSeq getData(){
+        return data;
+    }
+
+    @Override
+    public IParametersDomain getDomain() {
+        return new BSM_Domain();
+    }
+
+    @Override
+    public ISsqFunctionPoint ssqEvaluate(DoubleSeq parameters) {
+        return new BSM_Point(this, parameters.get(0), parameters.get(1),parameters.get(2));
+    }
+}
+
+class BSM_Point implements ISsqFunctionPoint{
+
+    private final BSM bsm;
+    private final double nstde;
+    private final double slstde;
+    private final double seasstde;
+    // we fix the std error of the trend (level)
+
+    public BSM_Point(BSM bsm, double ne, double sle, double sease){
+        this.bsm=bsm;
+        this.nstde=ne;
+        this.slstde=sle;
+        this.seasstde=sease;
+    }
+
+    @Override
+    public ISsqFunction getSsqFunction() {
+        return bsm;
+    }
+
+    @Override
+    public DoubleSeq getE() {
+       SsfData data= new SsfData(bsm.getData());
+       DiffuseLikelihood likelihood = DkToolkit.likelihood(ssf(), data, true, true);
+       return likelihood.deviances();
+    }
+
+    @Override
+    public DoubleSeq getParameters() {
+        return DoubleSeq.of(nstde, slstde, seasstde);
+    }
+
+    public Ssf ssf(){
+        StateComponent llt = LocalLinearTrend.stateComponent(.1, slstde*slstde);
+        StateComponent seas = SeasonalComponent.of(SeasonalModel.HarrisonStevens, 4, seasstde*seasstde);
+        StateComponent n = Noise.of(nstde*nstde);
+        CompositeSsf ssf = CompositeSsf.builder()
+                .add(llt, LocalLinearTrend.defaultLoading())
+                .add(seas, SeasonalComponent.defaultLoading())
+                .add(n, Noise.defaultLoading())
+                .build();
+        return ssf;
+
+    }
+}