diff --git a/src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicFitter.java b/src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicFitter.java
index 9c98392ad..75cbe9ff0 100644
--- a/src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicFitter.java
+++ b/src/mantissa/src/org/spaceroots/mantissa/fitting/HarmonicFitter.java
@@ -73,65 +73,6 @@ public class HarmonicFitter
     firstGuessNeeded = false;
   }
 
-  /**
-   * Simple constructor.
-   * @param maxIterations maximum number of iterations allowed
-   * @param convergence criterion threshold below which we do not need
-   * to improve the criterion anymore
-   * @param steadyStateThreshold steady state detection threshold, the
-   * problem has reached a steady state (read converged) if
-   * <code>Math.abs (Jn - Jn-1) < Jn * convergence</code>, where
-   * <code>Jn</code> and <code>Jn-1</code> are the current and
-   * preceding criterion value (square sum of the weighted residuals
-   * of considered measurements).
-   * @param epsilon threshold under which the matrix of the linearized
-   * problem is considered singular (see {@link
-   * org.spaceroots.mantissa.linalg.SquareMatrix#solve(
-   * org.spaceroots.mantissa.linalg.Matrix,double) SquareMatrix.solve}).
-   * @deprecated replaced by {@link #HarmonicFitter(Estimator)}
-   * as of version 7.0
-   */
-  public HarmonicFitter(int maxIterations, double convergence,
-                        double steadyStateThreshold, double epsilon) {
-    this(new GaussNewtonEstimator(maxIterations, convergence,
-                                   steadyStateThreshold, epsilon));
-  }
-
-  /**
-   * Simple constructor.
-
-   * <p>This constructor can be used when a first estimate of the
-   * coefficients is already known.</p>
-
-   * @param coefficients first estimate of the coefficients.
-   * A reference to this array is hold by the newly created
-   * object. Its elements will be adjusted during the fitting process
-   * and they will be set to the adjusted coefficients at the end.
-   * @param maxIterations maximum number of iterations allowed
-   * @param convergence criterion threshold below which we do not need
-   * to improve the criterion anymore
-   * @param steadyStateThreshold steady state detection threshold, the
-   * problem has reached a steady state (read converged) if
-   * <code>Math.abs (Jn - Jn-1) < Jn * convergence</code>, where
-   * <code>Jn</code> and <code>Jn-1</code> are the current and
-   * preceding criterion value (square sum of the weighted residuals
-   * of considered measurements).
-   * @param epsilon threshold under which the matrix of the linearized
-   * problem is considered singular (see {@link
-   * org.spaceroots.mantissa.linalg.SquareMatrix#solve(
-   * org.spaceroots.mantissa.linalg.Matrix,double) SquareMatrix.solve}).
-
-   * @deprecated replaced by {@link #HarmonicFitter(EstimatedParameter[],
-   * Estimator)} as of version 7.0
-   */
-  public HarmonicFitter(EstimatedParameter[] coefficients,
-                        int maxIterations, double convergence,
-                        double steadyStateThreshold, double epsilon) {
-    this(coefficients,
-          new GaussNewtonEstimator(maxIterations, convergence,
-                                   steadyStateThreshold, epsilon));
-  }
-
   public double[] fit()
     throws EstimationException {
     if (firstGuessNeeded) {
diff --git a/src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialFitter.java b/src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialFitter.java
index 4178a6af9..05c156fd6 100644
--- a/src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialFitter.java
+++ b/src/mantissa/src/org/spaceroots/mantissa/fitting/PolynomialFitter.java
@@ -78,78 +78,6 @@ public class PolynomialFitter
     super(coefficients, estimator);
   }
 
-  /** Simple constructor.
-
-   * <p>The polynomial fitter built this way are complete polynoms,
-   * ie. a n-degree polynom has n+1 coefficients. In order to build
-   * fitter for sparse polynoms (for example <code>a x^20 - b
-   * x^30</code>, on should first build the coefficients array and
-   * provide it to {@link
-   * #PolynomialFitter(PolynomialCoefficient[], int, double, double,
-   * double)}.</p>
-   * @param degree maximal degree of the polynom
-   * @param maxIterations maximum number of iterations allowed
-   * @param convergence criterion threshold below which we do not need
-   * to improve the criterion anymore
-   * @param steadyStateThreshold steady state detection threshold, the
-   * problem has reached a steady state (read converged) if
-   * <code>Math.abs (Jn - Jn-1) < Jn * convergence</code>, where
-   * <code>Jn</code> and <code>Jn-1</code> are the current and
-   * preceding criterion value (square sum of the weighted residuals
-   * of considered measurements).
-   * @param epsilon threshold under which the matrix of the linearized
-   * problem is considered singular (see {@link
-   * org.spaceroots.mantissa.linalg.SquareMatrix#solve(
-   * org.spaceroots.mantissa.linalg.Matrix,double) SquareMatrix.solve}).
- 
-   * @deprecated replaced by {@link #PolynomialFitter(int,Estimator)}
-   * as of version 7.0
-   */
-  public PolynomialFitter(int degree,
-                          int maxIterations, double convergence,
-                          double steadyStateThreshold, double epsilon) {
-    this(degree,
-         new GaussNewtonEstimator(maxIterations, steadyStateThreshold,
-                                  convergence, epsilon));
-  }
-
-  /** Simple constructor.
-
-   * <p>This constructor can be used either when a first estimate of
-   * the coefficients is already known (which is of little interest
-   * because the fit cost is the same whether a first guess is known or
-   * not) or when one needs to handle sparse polynoms like <code>a
-   * x^20 - b x^30</code>.</p>
-
-   * @param coefficients first estimate of the coefficients.
-   * A reference to this array is hold by the newly created
-   * object. Its elements will be adjusted during the fitting process
-   * and they will be set to the adjusted coefficients at the end.
-   * @param maxIterations maximum number of iterations allowed
-   * @param convergence criterion threshold below which we do not need
-   * to improve the criterion anymore
-   * @param steadyStateThreshold steady state detection threshold, the
-   * problem has reached a steady state (read converged) if
-   * <code>Math.abs (Jn - Jn-1) < Jn * convergence</code>, where
-   * <code>Jn</code> and <code>Jn-1</code> are the current and
-   * preceding criterion value (square sum of the weighted residuals
-   * of considered measurements).
-   * @param epsilon threshold under which the matrix of the linearized
-   * problem is considered singular (see {@link
-   * org.spaceroots.mantissa.linalg.SquareMatrix#solve(
-   * org.spaceroots.mantissa.linalg.Matrix,double) SquareMatrix.solve}).
-
-   * @deprecated replaced by {@link #PolynomialFitter(PolynomialCoefficient[],
-   * Estimator)} as of version 7.0
-   */
-  public PolynomialFitter(PolynomialCoefficient[] coefficients,
-                          int maxIterations, double convergence,
-                          double steadyStateThreshold, double epsilon) {
-    this(coefficients,
-         new GaussNewtonEstimator(maxIterations, steadyStateThreshold,
-                                  convergence, epsilon));
-  }
-
   /** Get the value of the function at x according to the current parameters value.
    * @param x abscissa at which the theoretical value is requested
    * @return theoretical value at x