Available Methods
- EMPTY_CLUSTER_IN_K_MEANS
- INPUT_ARRAY
- FRACTION
- AT_LEAST_ONE_COLUMN
- ZERO_NORM
- CANNOT_COMPUTE_NTH_ROOT_FOR_NEGATIVE_N
- AT_LEAST_ONE_ROW
- DIMENSIONS_MISMATCH_2x2 ( )
- EXPONENT
- LENGTH
- LOWER_BOUND_NOT_BELOW_UPPER_BOUND
- FUNCTION
- CONTINUED_FRACTION_NAN_DIVERGENCE
- INITIAL_COLUMN_AFTER_FINAL_COLUMN
- NO_SUCH_MATRIX_ENTRY
- NUMBER_OF_SAMPLES
- INITIAL_ROW_AFTER_FINAL_ROW
- NO_OPTIMUM_COMPUTED_YET
- CONTINUED_FRACTION_INFINITY_DIVERGENCE
- SIMPLE_MESSAGE
- VECTOR_MUST_HAVE_AT_LEAST_ONE_ELEMENT
- NON_CONVERGENT_CONTINUED_FRACTION
- NULL_NOT_ALLOWED
- STANDARD_DEVIATION
- NO_CONVERGENCE_WITH_ANY_START_POINT
- LOWER_ENDPOINT_ABOVE_UPPER_ENDPOINT
- TOO_SMALL_INTEGRATION_INTERVAL
- OUT_OF_BOUND_SIGNIFICANCE_LEVEL
- ZERO_DENOMINATOR
- MEAN
- OUT_OF_RANGE_SIMPLE
- OBJECT_TRANSFORMATION
- DIMENSION
- ROTATION_MATRIX_DIMENSIONS
- DIMENSIONS_MISMATCH_SIMPLE
- GCD_OVERFLOW_64_BITS ( )
- TOO_MANY_REGRESSORS
- CANNOT_NORMALIZE_A_ZERO_NORM_VECTOR
- POPULATION_SIZE
- CARDAN_ANGLES_SINGULARITY
- ZERO_DENOMINATOR_IN_FRACTION
- NUMBER_OF_POINTS
- FIRST_ROWS_NOT_INITIALIZED_YET
- NO_REGRESSORS
- MAX_EVALUATIONS_EXCEEDED
- NON_SQUARE_MATRIX
- WHOLE_FORMAT
- EMPTY_SELECTED_ROW_INDEX_ARRAY
- UNABLE_TO_ORTHOGONOLIZE_MATRIX
- DENOMINATOR
- NUMERATOR_FORMAT
- EQUAL_VERTICES_IN_SIMPLEX
- INDEX
- NO_DEGREES_OF_FREEDOM
- NOT_ENOUGH_DATA_FOR_NUMBER_OF_PREDICTORS
- FAILED_BRACKETING
- SHAPE
- DIMENSIONS_MISMATCH
- EMPTY_POLYNOMIALS_COEFFICIENTS_ARRAY
- FIRST_COLUMNS_NOT_INITIALIZED_YET
- COLUMN_INDEX
- REAL_FORMAT
- NO_DATA
- SIGNIFICANCE_LEVEL
- INSUFFICIENT_DIMENSION
- FAILED_FRACTION_CONVERSION
- INVALID_MAX_ITERATIONS
- ARRAY_SUMS_TO_ZERO
- TOO_LARGE_CUTOFF_SINGULAR_VALUE
- MAX_COUNT_EXCEEDED
- LIST_OF_CHROMOSOMES_BIGGER_THAN_POPULATION_SIZE
- NOT_POSITIVE_ELEMENT_AT_INDEX
- NOT_ENOUGH_POINTS_IN_SPLINE_PARTITION
- NORMALIZE_NAN
- NOT_FINITE_NUMBER
- OVERFLOW_IN_FRACTION
- POLYNOMIAL
- UNBOUNDED_SOLUTION
- NEGATIVE_ELEMENT_AT_INDEX
- INVALID_REGRESSION_OBSERVATION
- DENOMINATOR_FORMAT
- POPULATION_LIMIT_NOT_POSITIVE
- CONVERGENCE_FAILED
- OBSERVED_COUNTS_ALL_ZERO
- OUT_OF_BOUNDS_QUANTILE_VALUE
Related Classes
- java.util.Arrays
- java.io.BufferedReader
- org.junit.Assert
- java.text.ParseException
- java.security.MessageDigest
- java.math.BigDecimal
- java.math.BigInteger
- java.util.NoSuchElementException
- java.security.SecureRandom
- java.io.ObjectInputStream
- java.io.ObjectOutputStream
- java.lang.reflect.Array
- java.text.NumberFormat
- java.util.ConcurrentModificationException
- java.text.FieldPosition
- org.apache.commons.math.MathException
- org.apache.commons.math.util.MathUtils
- org.apache.commons.math.linear.RealMatrix
- org.apache.commons.math.stat.descriptive.moment.Mean
- org.apache.commons.math.complex.Complex
- org.apache.commons.math.linear.Array2DRowRealMatrix
- org.apache.commons.math.FunctionEvaluationException
- org.apache.commons.math.linear.ArrayRealVector
- org.apache.commons.math.stat.descriptive.SummaryStatistics
- org.apache.commons.math.ConvergenceException
Java Code Examples for org.apache.commons.math.exception.util.LocalizedFormats#INVALID_REGRESSION_OBSERVATION
The following examples show how to use
org.apache.commons.math.exception.util.LocalizedFormats#INVALID_REGRESSION_OBSERVATION .
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Example 1
Source File: MillerUpdatingRegression.java From astor with GNU General Public License v2.0 | 6 votes |
/** * Adds an observation to the regression model * @param x the array with regressor values * @param y the value of dependent variable given these regressors * @exception ModelSpecificationException if the length of {@code x} does not equal * the number of independent variables in the model */ public void addObservation(final double[] x, final double y) { if ((!this.hasIntercept && x.length != nvars) || (this.hasIntercept && x.length + 1 != nvars)) { throw new ModelSpecificationException(LocalizedFormats.INVALID_REGRESSION_OBSERVATION, x.length, nvars); } if (!this.hasIntercept) { include(MathUtils.copyOf(x, x.length), 1.0, y); } else { double[] tmp = new double[x.length + 1]; System.arraycopy(x, 0, tmp, 1, x.length); tmp[0] = 1.0; include(tmp, 1.0, y); } ++nobs; return; }
Example 2
Source File: MillerUpdatingRegression.java From astor with GNU General Public License v2.0 | 6 votes |
/** * Adds an observation to the regression model * @param x the array with regressor values * @param y the value of dependent variable given these regressors * @exception ModelSpecificationException if the length of {@code x} does not equal * the number of independent variables in the model */ public void addObservation(final double[] x, final double y) { if ((!this.hasIntercept && x.length != nvars) || (this.hasIntercept && x.length + 1 != nvars)) { throw new ModelSpecificationException(LocalizedFormats.INVALID_REGRESSION_OBSERVATION, x.length, nvars); } if (!this.hasIntercept) { include(MathUtils.copyOf(x, x.length), 1.0, y); } else { double[] tmp = new double[x.length + 1]; System.arraycopy(x, 0, tmp, 1, x.length); tmp[0] = 1.0; include(tmp, 1.0, y); } ++nobs; return; }