/** * Returns the <a href="http://www.xycoon.com/coefficient1.htm"> * coefficient of determination</a>, * usually denoted r-square. * <p> * <strong>Preconditions</strong>: <ul> * <li>At least two observations (with at least two different x values) * must have been added before invoking this method. If this method is * invoked before a model can be estimated, <code>Double,NaN</code> is * returned. * </li></ul></p> * * @return r-square */ public double getRSquare() { double ssto = getTotalSumSquares(); return (ssto - getSumSquaredErrors()) / ssto; }
/** * Returns the <a href="http://www.xycoon.com/coefficient1.htm"> * coefficient of determination</a>, * usually denoted r-square. * <p> * <strong>Preconditions</strong>: <ul> * <li>At least two observations (with at least two different x values) * must have been added before invoking this method. If this method is * invoked before a model can be estimated, <code>Double,NaN</code> is * returned. * </li></ul></p> * * @return r-square */ public double getRSquare() { double ssto = getTotalSumSquares(); return (ssto - getSumSquaredErrors()) / ssto; }
/** * Returns the <a href="http://www.xycoon.com/coefficient1.htm"> * coefficient of determination</a>, * usually denoted r-square. * <p> * <strong>Preconditions</strong>: <ul> * <li>At least two observations (with at least two different x values) * must have been added before invoking this method. If this method is * invoked before a model can be estimated, <code>Double,NaN</code> is * returned. * </li></ul></p> * * @return r-square */ public double getRSquare() { double ssto = getTotalSumSquares(); return (ssto - getSumSquaredErrors()) / ssto; }
map.put("slopeConfidenceInterval", regression.getSlopeConfidenceInterval()); map.put("interceptStdErr", regression.getInterceptStdErr()); map.put("totalSumSquares", regression.getTotalSumSquares()); map.put("significance", regression.getSignificance()); map.put("meanSquareError", regression.getMeanSquareError());
@Override LR.ModelResult asResult() { LR.ModelResult r = new LR.ModelResult(name, framework, hasConstant(), getNumVars(), state, getNTrain(), getNTest()); if (state != State.created) { List<Double> params = new ArrayList<>(); params.add(R.getIntercept()); params.add(R.getSlope()); r.withTrainInfo("parameters", params, "RSquared", R.getRSquare(), "significance", R.getSignificance(), "slope confidence interval", R.getSlopeConfidenceInterval(), "intercept std error", R.getInterceptStdErr(), "slope std error", R.getSlopeStdErr(), "SSE", R.getSumSquaredErrors(), "MSE", R.getMeanSquareError(), "correlation", R.getR(), "SSR", R.getRegressionSumSquares(), "SST", R.getTotalSumSquares()); } if (tester.isReady()) r.withTestInfo(tester.getStatistics()); return r; }