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From pste...@apache.org
Subject svn commit: r542048 - /jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/
Date Sun, 27 May 2007 23:02:14 GMT
Author: psteitz
Date: Sun May 27 16:02:13 2007
New Revision: 542048

URL: http://svn.apache.org/viewvc?view=rev&rev=542048
Log:
Javadoc formatting and minor edits.

Modified:
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimatedParameter.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationException.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationProblem.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/Estimator.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
    jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/WeightedMeasurement.java

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimatedParameter.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimatedParameter.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimatedParameter.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimatedParameter.java
Sun May 27 16:02:13 2007
@@ -19,16 +19,16 @@
 
 import java.io.Serializable;
 
-/** This class represent the estimated parameters of an estimation problem.
-
+/** This class represents the estimated parameters of an estimation problem.
+ *
  * <p>The parameters of an estimation problem have a name, a value and
  * a bound flag. The value of bound parameters is considered trusted
  * and the solvers should not adjust them. On the other hand, the
  * solvers should adjust the value of unbounds parameters until they
  * satisfy convergence criterions specific to each solver.</p>
-
+ *
  * @version $Id: EstimatedParameter.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public class EstimatedParameter

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationException.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationException.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationException.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationException.java
Sun May 27 16:02:13 2007
@@ -19,10 +19,11 @@
 
 import org.apache.commons.math.MathException;
 
-/** This class represents exceptions thrown by the estimation solvers.
-
+/** 
+ * This class represents exceptions thrown by the estimation solvers.
+ *
  * @version $Id: EstimationException.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public class EstimationException
@@ -31,7 +32,8 @@
     /** Serializable version identifier. */
     private static final long serialVersionUID = -7414806622114810487L;
 
-    /** Simple constructor.
+    /** 
+     * Simple constructor.
      * Build an exception by translating and formating a message
      * @param specifier format specifier (to be translated)
      * @param parts to insert in the format (no translation)
@@ -40,7 +42,8 @@
         super(specifier, parts);
     }
 
-    /** Simple constructor.
+    /** 
+     * Simple constructor.
      * Build an exception from a cause
      * @param cause cause of this exception
      */

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationProblem.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationProblem.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationProblem.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/EstimationProblem.java
Sun May 27 16:02:13 2007
@@ -17,12 +17,13 @@
 
 package org.apache.commons.math.estimation;
 
-/** This interface represents an estimation problem.
-
+/** 
+ * This interface represents an estimation problem.
+ *
  * <p>This interface should be implemented by all real estimation
  * problems before they can be handled by the estimators through the
  * {@link Estimator#estimate Estimator.estimate} method.</p>
-
+ *
  * <p>An estimation problem, as seen by a solver is a set of
  * parameters and a set of measurements. The parameters are adjusted
  * during the estimation through the {@link #getUnboundParameters
@@ -33,26 +34,29 @@
  * the parameters are adjusted. The purpose of the solver is to reduce
  * the residual between these values, it can retrieve the measurements
  * through the {@link #getMeasurements getMeasurements} method.</p>
-
+ *
  * @see Estimator
  * @see WeightedMeasurement
-
+ *
  * @version $Id: EstimationProblem.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public interface EstimationProblem {
-  /** Get the measurements of an estimation problem.
+  /** 
+   * Get the measurements of an estimation problem.
    * @return measurements
    */
   public WeightedMeasurement[] getMeasurements();
 
-  /** Get the unbound parameters of the problem.
+  /** 
+   * Get the unbound parameters of the problem.
    * @return unbound parameters
    */
   public EstimatedParameter[] getUnboundParameters();
 
-  /** Get all the parameters of the problem.
+  /** 
+   * Get all the parameters of the problem.
    * @return parameters
    */
   public EstimatedParameter[] getAllParameters();

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/Estimator.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/Estimator.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/Estimator.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/Estimator.java
Sun May 27 16:02:13 2007
@@ -17,46 +17,50 @@
 
 package org.apache.commons.math.estimation;
 
-/** This interface represents solvers for estimation problems.
-
+/**
+ * This interface represents solvers for estimation problems.
+ *
  * <p>The classes which are devoted to solve estimation problems
  * should implement this interface. The problems which can be handled
  * should implement the {@link EstimationProblem} interface which
  * gather all the information needed by the solver.</p>
-
+ *
  * <p>The interface is composed only of the {@link #estimate estimate}
  * method.</p>
-
+ *
  * @see EstimationProblem
-
+ *
  * @version $Id: Estimator.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public interface Estimator {
 
-  /** Solve an estimation problem.
-
+  /** 
+   * Solve an estimation problem.
+   *
    * <p>The method should set the parameters of the problem to several
    * trial values until it reaches convergence. If this method returns
    * normally (i.e. without throwing an exception), then the best
    * estimate of the parameters can be retrieved from the problem
    * itself, through the {@link EstimationProblem#getAllParameters
    * EstimationProblem.getAllParameters} method.</p>
-
+   *
    * @param problem estimation problem to solve
    * @exception EstimationException if the problem cannot be solved
-
+   *
    */
   public void estimate(EstimationProblem problem)
     throws EstimationException;
 
-  /** Get the Root Mean Square value.
+  /** 
+   * Get the Root Mean Square value.
    * Get the Root Mean Square value, i.e. the root of the arithmetic
    * mean of the square of all weighted residuals. This is related to the
    * criterion that is minimized by the estimator as follows: if
-   * <em>c</em> if the criterion, and <em>n</em> is the number of
-   * measurements, the the RMS is <em>sqrt (c/n)</em>.
+   * <em>c</em> is the criterion, and <em>n</em> is the number of
+   * measurements, then the RMS is <em>sqrt (c/n)</em>.
+   * 
    * @param problem estimation problem
    * @return RMS value
    */

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
Sun May 27 16:02:13 2007
@@ -23,39 +23,41 @@
 import org.apache.commons.math.linear.RealMatrix;
 import org.apache.commons.math.linear.RealMatrixImpl;
 
-/** This class implements a solver for estimation problems.
-
+/** 
+ * This class implements a solver for estimation problems.
+ *
  * <p>This class solves estimation problems using a weighted least
  * squares criterion on the measurement residuals. It uses a
  * Gauss-Newton algorithm.</p>
-
+ *
  * @version $Id: GaussNewtonEstimator.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public class GaussNewtonEstimator
   implements Estimator, Serializable {
 
-  /** Simple constructor.
-
-   * <p>This constructor build an estimator and store its convergence
+  /** 
+   * Simple constructor.
+   *
+   * <p>This constructor builds an estimator and stores its convergence
    * characteristics.</p>
-
+   *
    * <p>An estimator is considered to have converged whenever either
    * the criterion goes below a physical threshold under which
    * improvements are considered useless or when the algorithm is
    * unable to improve it (even if it is still high). The first
    * condition that is met stops the iterations.</p>
-
+   *
    * <p>The fact an estimator has converged does not mean that the
    * model accurately fits the measurements. It only means no better
    * solution can be found, it does not mean this one is good. Such an
    * analysis is left to the caller.</p>
-
+   *
    * <p>If neither conditions are fulfilled before a given number of
    * iterations, the algorithm is considered to have failed and an
    * {@link EstimationException} is thrown.</p>
-
+   *
    * @param maxIterations maximum number of iterations allowed
    * @param convergence criterion threshold below which we do not need
    * to improve the criterion anymore
@@ -74,14 +76,15 @@
     this.convergence          = convergence;
   }
 
-  /** Solve an estimation problem using a least squares criterion.
-
+  /** 
+   * Solve an estimation problem using a least squares criterion.
+   *
    * <p>This method set the unbound parameters of the given problem
    * starting from their current values through several iterations. At
    * each step, the unbound parameters are changed in order to
    * minimize a weighted least square criterion based on the
    * measurements of the problem.</p>
-
+   *
    * <p>The iterations are stopped either when the criterion goes
    * below a physical threshold under which improvement are considered
    * useless or when the algorithm is unable to improve it (even if it
@@ -89,12 +92,12 @@
    * iterations. If the convergence it nos reached before the maximum
    * number of iterations, an {@link EstimationException} is
    * thrown.</p>
-
+   *
    * @param problem estimation problem to solve
    * @exception EstimationException if the problem cannot be solved
-
+   *
    * @see EstimationProblem
-
+   *
    */
   public void estimate(EstimationProblem problem)
     throws EstimationException {
@@ -124,20 +127,21 @@
 
   }
 
-  /** Estimate the solution of a linear least square problem.
-
+  /** 
+   * Estimate the solution of a linear least square problem.
+   *
    * <p>The Gauss-Newton algorithm is iterative. Each iteration
-   * consist in solving a linearized least square problem. Several
+   * consists in solving a linearized least square problem. Several
    * iterations are needed for general problems since the
    * linearization is only an approximation of the problem
    * behaviour. However, for linear problems one iteration is enough
    * to get the solution. This method is provided in the public
    * interface in order to handle more efficiently these linear
    * problems.</p>
-
+   *
    * @param problem estimation problem to solve
    * @exception EstimationException if the problem cannot be solved
-
+   *
    */
   public void linearEstimate(EstimationProblem problem)
     throws EstimationException {
@@ -210,7 +214,8 @@
 
   }
 
-  /** Get the Root Mean Square value.
+  /** 
+   * Get the Root Mean Square value.
    * Get the Root Mean Square value, i.e. the root of the arithmetic
    * mean of the square of all weighted residuals. This is related to the
    * criterion that is minimized by the estimator as follows: if

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
Sun May 27 16:02:13 2007
@@ -19,15 +19,16 @@
 import java.io.Serializable;
 import java.util.Arrays;
 
-/** This class solves a least squares problem.
-
+/** 
+ * This class solves a least squares problem.
+ *
  * <p>This implementation <em>should</em> work even for over-determined
systems
  * (i.e. systems having more variables than equations). Over-determined systems
  * are solved by ignoring the variables which have the smallest impact according
  * to their jacobian column norm. Only the rank of the matrix and some loop bounds
  * are changed to implement this. This feature has undergone only basic testing
  * for now and should still be considered experimental.</p>
-
+ *
  * <p>The resolution engine is a simple translation of the MINPACK <a
  * href="http://www.netlib.org/minpack/lmder.f">lmder</a> routine with minor
  * changes. The changes include the over-determined resolution and the Q.R.
@@ -37,7 +38,7 @@
  * redistribution policy for MINPACK is available <a
  * href="http://www.netlib.org/minpack/disclaimer">here</a>, for convenience, it
  * is reproduced below.</p>
-
+ *
  * <table border="0" width="80%" cellpadding="10" align="center" bgcolor="#E0E0E0">
  * <tr><td>
  *    Minpack Copyright Notice (1999) University of Chicago.
@@ -93,7 +94,8 @@
  */
 public class LevenbergMarquardtEstimator implements Serializable, Estimator {
 
-  /** Build an estimator for least squares problems.
+  /** 
+   * Build an estimator for least squares problems.
    * <p>The default values for the algorithm settings are:
    *   <ul>
    *    <li>{@link #setInitialStepBoundFactor initial step bound factor}: 100.0</li>
@@ -113,10 +115,12 @@
     setOrthoTolerance(1.0e-10);
   }
 
-  /** Set the positive input variable used in determining the initial step bound.
+  /** 
+   * Set the positive input variable used in determining the initial step bound.
    * This bound is set to the product of initialStepBoundFactor and the euclidean norm of
diag*x if nonzero,
    * or else to initialStepBoundFactor itself. In most cases factor should lie
    * in the interval (0.1, 100.0). 100.0 is a generally recommended value
+   * 
    * @param initialStepBoundFactor initial step bound factor
    * @see #estimate
    */
@@ -124,15 +128,19 @@
     this.initialStepBoundFactor = initialStepBoundFactor;
   }
 
-  /** Set the maximal number of cost evaluations.
-  * @param maxCostEval maximal number of cost evaluations
+  /** 
+   * Set the maximal number of cost evaluations.
+   * 
+   * @param maxCostEval maximal number of cost evaluations
    * @see #estimate
   */
   public void setMaxCostEval(int maxCostEval) {
     this.maxCostEval = maxCostEval;
   }
 
-  /** Set the desired relative error in the sum of squares.
+  /** 
+   * Set the desired relative error in the sum of squares.
+   * 
    * @param costRelativeTolerance desired relative error in the sum of squares
    * @see #estimate
    */
@@ -140,7 +148,9 @@
     this.costRelativeTolerance = costRelativeTolerance;
   }
 
-  /** Set the desired relative error in the approximate solution parameters.
+  /** 
+   * Set the desired relative error in the approximate solution parameters.
+   * 
    * @param parRelativeTolerance desired relative error
    * in the approximate solution parameters
    * @see #estimate
@@ -149,7 +159,9 @@
     this.parRelativeTolerance = parRelativeTolerance;
   }
 
-  /** Set the desired max cosine on the orthogonality.
+  /** 
+   * Set the desired max cosine on the orthogonality.
+   * 
    * @param orthoTolerance desired max cosine on the orthogonality
    * between the function vector and the columns of the jacobian
    * @see #estimate
@@ -158,21 +170,26 @@
     this.orthoTolerance = orthoTolerance;
   }
 
-  /** Get the number of cost evaluations.
+  /** 
+   * Get the number of cost evaluations.
+   * 
    * @return number of cost evaluations
    * */
   public int getCostEvaluations() {
     return costEvaluations;
   }
 
-  /** Get the number of jacobian evaluations.
+  /** 
+   * Get the number of jacobian evaluations.
+   * 
    * @return number of jacobian evaluations
    * */
   public int getJacobianEvaluations() {
     return jacobianEvaluations;
   }
 
-  /** Update the jacobian matrix.
+  /** 
+   * Update the jacobian matrix.
    */
   private void updateJacobian() {
     ++jacobianEvaluations;
@@ -186,7 +203,8 @@
     }
   }
 
-  /** Update the residuals array and cost function value.
+  /** 
+   * Update the residuals array and cost function value.
    */
   private void updateResidualsAndCost() {
     ++costEvaluations;
@@ -200,12 +218,14 @@
     cost = Math.sqrt(cost);
   }
 
-  /** Get the Root Mean Square value.
+  /** 
+   * Get the Root Mean Square value.
    * Get the Root Mean Square value, i.e. the root of the arithmetic
    * mean of the square of all weighted residuals. This is related to the
    * criterion that is minimized by the estimator as follows: if
    * <em>c</em> if the criterion, and <em>n</em> is the number of
    * measurements, then the RMS is <em>sqrt (c/n)</em>.
+   * 
    * @param problem estimation problem
    * @return RMS value
    */
@@ -219,7 +239,8 @@
     return Math.sqrt(criterion / wm.length);
   }
 
-  /** Solve an estimation problem using the Levenberg-Marquardt algorithm.
+  /** 
+   * Solve an estimation problem using the Levenberg-Marquardt algorithm.
    * <p>The algorithm used is a modified Levenberg-Marquardt one, based
    * on the MINPACK <a href="http://www.netlib.org/minpack/lmder.f">lmder</a>
    * routine. The algorithm settings must have been set up before this method
@@ -236,6 +257,7 @@
    *   <li>Jorge   J. More</li>
    *   </ul>
    * <p>Luc Maisonobe did the Java translation.</p>
+   * 
    * @param problem estimation problem to solve
    * @exception EstimationException if convergence cannot be
    * reached with the specified algorithm settings or if there are more variables
@@ -493,7 +515,8 @@
 
   }
 
-  /** Determine the Levenberg-Marquardt parameter.
+  /** 
+   * Determine the Levenberg-Marquardt parameter.
    * <p>This implementation is a translation in Java of the MINPACK
    * <a href="http://www.netlib.org/minpack/lmpar.f">lmpar</a>
    * routine.</p>
@@ -506,6 +529,7 @@
    *   <li>Jorge   J. More</li>
    * </ul>
    * <p>Luc Maisonobe did the Java translation.</p>
+   * 
    * @param qy array containing qTy
    * @param delta upper bound on the euclidean norm of diagR * lmDir
    * @param diag diagonal matrix
@@ -661,7 +685,8 @@
     }
   }
 
-  /** Solve a*x = b and d*x = 0 in the least squares sense.
+  /** 
+   * Solve a*x = b and d*x = 0 in the least squares sense.
    * <p>This implementation is a translation in Java of the MINPACK
    * <a href="http://www.netlib.org/minpack/qrsolv.f">qrsolv</a>
    * routine.</p>
@@ -674,6 +699,7 @@
    *   <li>Jorge   J. More</li>
    * </ul>
    * <p>Luc Maisonobe did the Java translation.</p>
+   * 
    * @param qy array containing qTy
    * @param diag diagonal matrix
    * @param lmDiag diagonal elements associated with lmDir
@@ -783,7 +809,8 @@
 
   }
 
-  /** Decompose a matrix A as A.P = Q.R using Householder transforms.
+  /** 
+   * Decompose a matrix A as A.P = Q.R using Householder transforms.
    * <p>As suggested in the P. Lascaux and R. Theodor book
    * <i>Analyse num&eacute;rique matricielle appliqu&eacute;e &agrave;
    * l'art de l'ing&eacute;nieur</i> (Masson, 1986), instead of representing
@@ -872,7 +899,9 @@
 
   }
 
-  /** Compute the product Qt.y for some Q.R. decomposition.
+  /** 
+   * Compute the product Qt.y for some Q.R. decomposition.
+   * 
    * @param y vector to multiply (will be overwritten with the result)
    */
   private void qTy(double[] y) {
@@ -896,7 +925,8 @@
   /** Array of parameters. */
   private EstimatedParameter[] parameters;
 
-  /** Jacobian matrix.
+  /** 
+   * Jacobian matrix.
    * <p>Depending on the computation phase, this matrix is either in
    * canonical form (just after the calls to updateJacobian) or in
    * Q.R. decomposed form (after calls to qrDecomposition)</p>

Modified: jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/WeightedMeasurement.java
URL: http://svn.apache.org/viewvc/jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/WeightedMeasurement.java?view=diff&rev=542048&r1=542047&r2=542048
==============================================================================
--- jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/WeightedMeasurement.java
(original)
+++ jakarta/commons/proper/math/trunk/src/java/org/apache/commons/math/estimation/WeightedMeasurement.java
Sun May 27 16:02:13 2007
@@ -19,14 +19,15 @@
 
 import java.io.Serializable;
 
-/** This class represents measurements in estimation problems.
-
+/** 
+ * This class represents measurements in estimation problems.
+ *
  * <p>This abstract class implements all the methods needed to handle
  * measurements in a general way. It defines neither the {@link
  * #getTheoreticalValue getTheoreticalValue} nor the {@link
  * #getPartial getPartial} methods, which should be defined by
  * sub-classes according to the specific problem.</p>
-
+ *
  * <p>The {@link #getTheoreticalValue getTheoreticalValue} and {@link
  * #getPartial getPartial} methods must always use the current
  * estimate of the parameters set by the solver in the problem. These
@@ -35,27 +36,29 @@
  * EstimationProblem.getAllParameters} method if the measurements are
  * independant of the problem, or directly if they are implemented as
  * inner classes of the problem.</p>
-
+ *
  * <p>The instances for which the <code>ignored</code> flag is set
  * through the {@link #setIgnored setIgnored} method are ignored by the
  * solvers. This can be used to reject wrong measurements at some
  * steps of the estimation.</p>
-
+ *
  * @see EstimationProblem
-
+ *
  * @version $Id: WeightedMeasurement.java 1705 2006-09-17 19:57:39Z luc $
-
+ *
  */
 
 public abstract class WeightedMeasurement implements Serializable {
 
-  /** Simple constructor.
+  /** 
+   * Simple constructor.
    * Build a measurement with the given parameters, and set its ignore
    * flag to false.
    * @param weight weight of the measurement in the least squares problem
    * (two common choices are either to use 1.0 for all measurements, or to
    * use a value proportional to the inverse of the variance of the measurement
    * type)
+   * 
    * @param measuredValue measured value
    */
   public WeightedMeasurement(double weight, double measuredValue) {
@@ -65,7 +68,9 @@
   }
 
   /** Simple constructor.
+   * 
    * Build a measurement with the given parameters
+   * 
    * @param weight weight of the measurement in the least squares problem
    * @param measuredValue measured value
    * @param ignored true if the measurement should be ignored
@@ -77,41 +82,51 @@
     this.ignored       = ignored;
   }
 
-  /** Get the weight of the measurement in the least squares problem
+  /** 
+   * Get the weight of the measurement in the least squares problem
+   * 
    * @return weight
    */
   public double getWeight() {
     return weight;
   }
 
-  /** Get the measured value
+  /** 
+   * Get the measured value
+   * 
    * @return measured value
    */
   public double getMeasuredValue() {
     return measuredValue;
   }
 
-  /** Get the residual for this measurement
+  /** 
+   * Get the residual for this measurement
    * The residual is the measured value minus the theoretical value.
+   * 
    * @return residual
    */
   public double getResidual() {
     return measuredValue - getTheoreticalValue();
   }
 
-  /** Get the theoretical value expected for this measurement
+  /** 
+   * Get the theoretical value expected for this measurement
    * <p>The theoretical value is the value expected for this measurement
    * if the model and its parameter were all perfectly known.</p>
    * <p>The value must be computed using the current estimate of the parameters
    * set by the solver in the problem.</p>
+   * 
    * @return theoretical value
    */
   public abstract double getTheoreticalValue();
 
-  /** Get the partial derivative of the {@link #getTheoreticalValue
+  /** 
+   * Get the partial derivative of the {@link #getTheoreticalValue
    * theoretical value} according to the parameter.
    * <p>The value must be computed using the current estimate of the parameters
    * set by the solver in the problem.</p>
+   * 
    * @param parameter parameter against which the partial derivative
    * should be computed
    * @return partial derivative of the {@link #getTheoreticalValue
@@ -119,16 +134,20 @@
    */
   public abstract double getPartial(EstimatedParameter parameter);
 
-  /** Set the ignore flag to the specified value
+  /** 
+   * Set the ignore flag to the specified value
    * Setting the ignore flag to true allow to reject wrong
    * measurements, which sometimes can be detected only rather late.
+   * 
    * @param ignored value for the ignore flag
    */
   public void setIgnored(boolean ignored) {
     this.ignored = ignored;
   }
 
-  /** Check if this measurement should be ignored
+  /** 
+   * Check if this measurement should be ignored
+   * 
    * @return true if the measurement should be ignored
    */
   public boolean isIgnored() {



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