Uses of Class
org.apache.commons.math3.exception.NullArgumentException

Compute this ÷ a.

Compute this - a.

Computes the value of the gradient at x.

Computes the value of the gradient at x.

Computes the value of the Gaussian at x.

Computes the value of the sigmoid at x.

Computes the value of the sigmoid at x.

Integrate the function in the given interval.

Interpolate value and first derivatives at a specified abscissa.

Computes an interpolating function for the data set.

Compute an interpolating function for the dataset.

Interpolate value at a specified abscissa.

Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.

Simple mathematical function.

Construct a Newton polynomial with the given a[] and c[].

This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0.

Prepare for computation.

Solve for a zero in the given interval, start at startValue.

Convenience method to find a zero of a univariate real function.

Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.

Find a complex root for the polynomial with the given coefficients, starting from the given initial value.

Check that the endpoints specify an interval and the end points bracket a root.

Returns a Complex whose value is (this / divisor).

Returns a Complex whose value is this * factor.

Returns a Complex whose value is (this - subtrahend).

Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.

Create an instance with a custom number format for both real and imaginary parts.

Solve for a zero in the given interval, start at startValue.

Correct the current state estimate with an actual measurement.

Create a new ProcessModel, taking double arrays as input parameters.

Creates a new Kalman filter with the given process and measurement models.

Creates a new ListPopulation instance.

Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.

Check if submatrix ranges indices are valid.

Copy a submatrix.

Copy a submatrix.

Creates a column FieldMatrix using the data from the input array.

Returns a FieldMatrix whose entries are the the values in the the input array.

Returns a RealMatrix whose entries are the the values in the the input array.

Create a row FieldMatrix using the data from the input array.

Get the elements type from an array.

Gets a submatrix.

Gets a submatrix.

Computes the inverse of the given matrix.

Map an addition operation to each entry.

Map an addition operation to each entry.

Map an addition operation to each entry.

Map a division operation to each entry.

Map a division operation to each entry.

Map a division operation to each entry.

Map a multiplication operation to each entry.

Map a multiplication operation to each entry.

Map a multiplication operation to each entry.

Map a subtraction operation to each entry.

Map a subtraction operation to each entry.

Map a subtraction operation to each entry.

Replace the submatrix starting at (row, column) using data in the input subMatrix array.

Replace the submatrix starting at (row, column) using data in the input subMatrix array.

Replace the submatrix starting at (row, column) using data in the input subMatrix array.

Replace the submatrix starting at (row, column) using data in the input subMatrix array.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns the solution to the system (A - shift · I) · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Returns an estimate of the solution to the linear system A · x = b.

Create a new FieldMatrix<T> using the input array as the underlying data array.

Create a new FieldMatrix<T> using the input array as the underlying data array.

Create a new RealMatrix using the input array as the underlying data array.

Create a new ArrayFieldVector using the input array as the underlying data array.

Construct a vector by appending one vector to another vector.

Construct a vector from another vector.

Deprecated.

Construct a vector by appending one vector to another vector.

Construct a vector from an array, copying the input array.

Construct a vector from part of a array.

Construct a vector by appending one vector to another vector.

Create a new ArrayRealVector using the input array as the underlying data array.

Construct a vector from part of an array.

Construct a vector from another vector, using a deep copy.

Creates a matrix using the input array as the underlying data.

Creates a new instance of this class, with custom iteration manager.

Computes the empirical distribution using values from the file in valuesFileURL and binCount bins.

Computes the empirical distribution from the input file.

Create a new generator.

Merge another Frequency object's counts into this instance.

Copies source to dest.

Copies source to dest.

Copy constructor.

A copy constructor.

Copies source to dest.

Copies source to dest.

Copies source to dest.

Copies source to dest.

Copy constructor, creates a new Kurtosis identical to the original

Copy constructor, creates a new SecondMoment identical to the original

Copy constructor, creates a new Skewness identical to the original

Copy constructor, creates a new Variance identical to the original

Copies source to dest.

Copy constructor, creates a new Median identical to the original

Copy constructor, creates a new Percentile identical to the original

Copies source to dest.

Copies source to dest.

Copy constructor, creates a new Sum identical to the original

Copy constructor, creates a new SumOfSquares identical to the original

Computes the ANOVA P-value for a collection of double[] arrays.

Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.

Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha.

Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, under the assumption of equal subpopulation variances.

Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.

Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.

Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length.

Computes a paired, 2-sample t-statistic based on the data in the input arrays.

Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between sample1 and sample2 is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level alpha.

Computes a t statistic given observed values and a comparison constant.

Computes a 2-sample t statistic , comparing the means of the datasets described by two StatisticalSummary instances, without the assumption of equal subpopulation variances.

Performs a two-sided t-test evaluating the null hypothesis that sample1 and sample2 are drawn from populations with the same mean, with significance level alpha.

Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which sample is drawn equals mu.

Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by stats is drawn equals mu.

Performs a two-sided t-test evaluating the null hypothesis that sampleStats1 and sampleStats2 describe datasets drawn from populations with the same mean, with significance level alpha.

Returns the observed significance level, or p-value, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.

Checks that an object is not null.

Calculates the convolution between two sequences.

Sort an array in ascending order in place and perform the same reordering of entries on other arrays.

Constructor with specified pivoting strategy