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p
P, such that
P %*% A == L %*% U
P pivoting matrix in the QR decomposition.
P, the pivoting matrix in the QR decomposition.
P as in
P %*% A == L %*% U
P as in LUx = PAx = Pb
Runtime.getRuntime().availableProcessors()
Poisson.
Poisson with an overriding link function.
Poisson.
Poisson with an overriding link function.
UnivariateRealFunction that represents a finite length expression constructed from variables and constants,
using the operations of addition, subtraction, multiplication, and constant non-negative whole number exponents.Polyroot instance to solve polynomial equations.
pos before using, e.g., ++pos.
- position() -
Method in class com.numericalmethod.suanshu.stats.timeseries.TimeSeries.Iterator
- Get the current position in reading the time series.
- POSITIVE_INFINITY -
Static variable in class com.numericalmethod.suanshu.number.complex.Complex
- a number representing the positive infinity of type Complex
- positiveDefinite(Matrix) -
Static method in class com.numericalmethod.suanshu.matrix.doubles.IsMatrix
- Check if a square matrix is positive definite.
- positiveSemiDefinite(Matrix) -
Static method in class com.numericalmethod.suanshu.matrix.doubles.IsMatrix
- Deprecated. Not supported yet.
- pow(double) -
Method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.SparseVector
-
- Pow - Class in com.numericalmethod.suanshu.matrix.doubles.operation
- This computes a square DenseMatrix
A to the power of integer n, An. - Pow(Matrix, int, double) -
Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.Pow
- Construct the matrix
Aexponent so that
Aexponent = basescale * B
- Pow(Matrix, int) -
Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.Pow
- Construct the matrix
Aexponent so that
Aexponent = (1e100)scale * B
- pow(BigDecimal, BigDecimal) -
Static method in class com.numericalmethod.suanshu.number.big.BigDecimalUtils
- Compute
a to the power of b.
- pow(BigDecimal, BigDecimal, int) -
Static method in class com.numericalmethod.suanshu.number.big.BigDecimalUtils
- Compute
a to the power of b.
- pow(BigDecimal, int) -
Static method in class com.numericalmethod.suanshu.number.big.BigDecimalUtils
- Compute
a to the power of b where n is an integer.
- pow(BigDecimal, int, int) -
Static method in class com.numericalmethod.suanshu.number.big.BigDecimalUtils
- Compute
a to the power of b where b is an integer.
- pow(Complex, Complex) -
Static method in class com.numericalmethod.suanshu.number.complex.ElementaryFunction
z1 to the power z2.
- pow(double) -
Method in class com.numericalmethod.suanshu.vector.doubles.dense.DenseVector
-
- pow(double) -
Method in class com.numericalmethod.suanshu.vector.doubles.ImmutableVector
-
- pow(double) -
Method in interface com.numericalmethod.suanshu.vector.doubles.Vector
v ^ s
Take the exponentiation of all entries in the vector v by a scalar.
- Powell - Class in com.numericalmethod.suanshu.optimization.unconstrained.conjugatedirection
- Powell's algorithm, starting from an initial point, performs a series
of line searches in one iteration.
- Powell() -
Constructor for class com.numericalmethod.suanshu.optimization.unconstrained.conjugatedirection.Powell
-
- PowerLawSingularity - Class in com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution
- This transformation is good for an integral which diverges at one of the end points.
- PowerLawSingularity(PowerLawSingularity.Type, double, double, double) -
Constructor for class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution.PowerLawSingularity
- Construct an instance of the PowerLawSingularity substitution rule.
- PowerLawSingularity.Type - Enum in com.numericalmethod.suanshu.analysis.integration.univariate.riemann.substitution
- the type of end point divergence
- precision() -
Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.ChangeOfVariable
-
- precision -
Variable in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.EulerMaclaurin
- the convergence threshold
The iterative procedure converges when the relative difference between two successive sums is less than
precision.
- precision() -
Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.EulerMaclaurin
-
- precision() -
Method in interface com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Integrator
- Get the convergence threshold.
- precision -
Variable in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Riemann
- the convergence threshold
- precision() -
Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Riemann
-
- precision() -
Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Romberg
-
- precision -
Variable in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Simpson
- the convergence threshold
- precision() -
Method in class com.numericalmethod.suanshu.analysis.integration.univariate.riemann.Simpson
-
- precision -
Variable in class com.numericalmethod.suanshu.matrix.doubles.operation.PseudoInverse
- the precision used to truncate the negligible singular values
- Preconditioner - Interface in com.numericalmethod.suanshu.matrix.doubles.matrixtype.sparse.solver.iterative.preconditioner
- Preconditioning is usually used to reduce the condition number of the
coefficient matrix of a linear system, so as to accelerate the convergence
when the system is solved by an iterative method.
- previousWeekDay(DateTime) -
Static method in class com.numericalmethod.suanshu.time.JodaTimeUtils
- Get the previous weekday, i.e., skipping Saturdays and Sundays.
- pricing(Tableau) -
Method in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.pivoting.NaiveRule
- pivot column selection (pricing):
We choose the column with most negative reduced cost (last entry in the column).
- pricing(Tableau) -
Method in interface com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.pivoting.SimplexPivoting
- pivot column selection (pricing)
- pricing(Tableau) -
Method in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.pivoting.SmallestSubscriptRule
- pivot column selection (pricing):
The pivot column is the smallest non-basic variable index, s, such that
column s has a negative element in the bottom row (reduced cost).
- prob -
Variable in class com.numericalmethod.suanshu.stats.test.distribution.pearson.AS159.RandomMatrix
- the probability of observing this matrix
- ProbabilityMassFunction<X> - Interface in com.numericalmethod.suanshu.stats.distribution
- A probability mass function (pmf) is a function that gives the probability that a discrete random variable is exactly equal to some value.
- Probit - Class in com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.link
- This class represents the link function:
Inverse of cumulative distribution function of a NormalDistribution distribution N(0, 1).
- Probit() -
Constructor for class com.numericalmethod.suanshu.stats.regression.linear.glm.distribution.link.Probit
-
- problem -
Variable in class com.numericalmethod.suanshu.optimization.minmax.LeastPth
- the minmax problem to be solved
- problem -
Variable in class com.numericalmethod.suanshu.stats.regression.linear.glm.GeneralizedLinearModel
- the generalized linear regression problem to be solved
- problem -
Variable in class com.numericalmethod.suanshu.stats.regression.linear.glm.quasi.GeneralizedLinearModelQuasiFamily
- the quasi- generalized linear regression problem to be solved
- problem -
Variable in class com.numericalmethod.suanshu.stats.regression.linear.logistic.Logistic
- the logistic regression problem to be solved
- problem -
Variable in class com.numericalmethod.suanshu.stats.regression.linear.ols.OlsRegression
- the ordinary linear regression problem to be solved
- problem -
Variable in class com.numericalmethod.suanshu.stats.regression.linear.Residuals
- the linear regression problem to be solved
- problemSize() -
Method in class com.numericalmethod.suanshu.optimization.constrained.linearprogramming.simplex.Tableau
- Get the number of variables in the problem, the cost/objective function.
- product(GivensMatrix[]) -
Static method in class com.numericalmethod.suanshu.matrix.doubles.matrixtype.GivensMatrix
- Given Givens matrices
{Gi},
compute G, where
G = G1 %*% ... %*% G2 %*% Gn
- product(Householder[], int, int, int, int) -
Static method in class com.numericalmethod.suanshu.matrix.doubles.operation.Householder
- Given Householder matrices
{Qi},
compute Q.
- product(Householder[], int, int) -
Static method in class com.numericalmethod.suanshu.matrix.doubles.operation.Householder
- Given Householder matrix
{Qi},
compute Q, where
Q = Q1 %*% Q2 %*% ... %*% Qn %*% I
To compute Q,
instead of explicitly doing this multiplication, we can improve the performance
by applying Qi's repeatedly on the Identity matrix.
- Projection - Class in com.numericalmethod.suanshu.analysis.function.rn2r1
- This class creates a real-valued function
RealScalarFunction from a vector-valued function RealVectorFunction by
taking only one of its coordinate components in the vector output. - Projection(RealVectorFunction, int) -
Constructor for class com.numericalmethod.suanshu.analysis.function.rn2r1.Projection
- Construct a Rn → R1 projection from the Rn → Rm function
f.
- Projection - Class in com.numericalmethod.suanshu.vector.doubles.dense.operation
- Project a vector
v on another vector w
or a set of vectors (basis) {wi}. - Projection(Vector, VectorList) -
Constructor for class com.numericalmethod.suanshu.vector.doubles.dense.operation.Projection
- Construct a projection of a vector
v onto a set of basis {wi}.
- Projection(Vector, Vector[]) -
Constructor for class com.numericalmethod.suanshu.vector.doubles.dense.operation.Projection
- Construct a projection of a vector
v onto a set of basis {wi}.
- Projection(Vector, Vector) -
Constructor for class com.numericalmethod.suanshu.vector.doubles.dense.operation.Projection
- Construct a projection of a vector
v onto another vector.
- projVector -
Variable in class com.numericalmethod.suanshu.vector.doubles.dense.operation.Projection
- the projected vectors of
v on {wi}
It lies on the hyperplane of {wi}.
- property(Number) -
Method in class com.numericalmethod.suanshu.matrix.doubles.factorization.eigen.Eigen
- Get a Property object by its eigenvalue.
- PseudoInverse - Class in com.numericalmethod.suanshu.matrix.doubles.operation
- The Moore–Penrose pseudoinverse of an
m x n matrix A is A+. - PseudoInverse(Matrix, double) -
Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.PseudoInverse
- Construct the Moore–Penrose pseudoinverse matrix of
A.
- PseudoInverse(Matrix) -
Constructor for class com.numericalmethod.suanshu.matrix.doubles.operation.PseudoInverse
- Construct the Moore–Penrose pseudoinverse matrix of
A.
- psi -
Variable in class com.numericalmethod.suanshu.optimization.unconstrained.quasinewton.Huang
- ψ,
a Huang family parameterization
- psi -
Variable in class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.ArimaxModel
- the coefficients of the deterministic terms (excluding the intercept term)
- psi() -
Method in class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.ArimaxModel
- Get the coefficients of the deterministic terms.
- PSI -
Variable in class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.LinearRepresentation
- the coefficients of the linear representation of the time series
- psi() -
Method in class com.numericalmethod.suanshu.stats.timeseries.linear.multivariate.stationaryprocess.arima.arma.Vecm
- Get the coefficients of the deterministic terms.
- psi -
Variable in class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaxModel
- the coefficients of the deterministic terms (excluding the intercept term)
- psi() -
Method in class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaxModel
- Get the coefficients of the deterministic terms.
- psi() -
Method in class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.arma.LinearRepresentation
- Get a copy of the linear representation coefficients.
- pValue -
Variable in class com.numericalmethod.suanshu.stats.test.HypothesisTest
- p-value for the test statistics
- pValue() -
Method in class com.numericalmethod.suanshu.stats.test.HypothesisTest
- Get the p-value.
- pValue(double) -
Method in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonRankSumDistribution
- Compute the two-sided p-value for a critical value.
- pValue(double) -
Method in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonSignedRankDistribution
- Compute the two-sided p-value for a critical value.
- pValue1SidedGreater -
Variable in class com.numericalmethod.suanshu.stats.test.mean.T
- right, one-sided p-value
- pValue1SidedGreater -
Variable in class com.numericalmethod.suanshu.stats.test.rank.SiegelTukey
- right, one-sided p-value
- pValue1SidedGreater -
Variable in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonRankSum
- right, one-sided p-value
- pValue1SidedGreater(double) -
Method in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonRankSumDistribution
- Compute the one-sided p-value for the statistics greater than a critical value.
- pValue1SidedGreater -
Variable in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonSignedRank
- right, one-sided p-value
- pValue1SidedGreater(double) -
Method in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonSignedRankDistribution
- Compute the one-sided p-value for the statistics greater than a critical value.
- pValue1SidedGreater -
Variable in class com.numericalmethod.suanshu.stats.test.variance.F
- right, one-sided p-value
- pValue1SidedLess -
Variable in class com.numericalmethod.suanshu.stats.test.mean.T
- left, one-sided p-value
- pValue1SidedLess -
Variable in class com.numericalmethod.suanshu.stats.test.rank.SiegelTukey
- left, one-sided p-value
- pValue1SidedLess -
Variable in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonRankSum
- left, one-sided p-value
- pValue1SidedLess -
Variable in class com.numericalmethod.suanshu.stats.test.rank.wilcoxon.WilcoxonSignedRank
- left, one-sided p-value
- pValue1SidedLess -
Variable in class com.numericalmethod.suanshu.stats.test.variance.F
- left, one-sided p-value
- pvalueZ1 -
Variable in class com.numericalmethod.suanshu.stats.test.distribution.normality.DAgostino
- the p-value for Z1
- pvalueZ2 -
Variable in class com.numericalmethod.suanshu.stats.test.distribution.normality.DAgostino
- the p-value for Z2
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SuanShu, a Java numerical and statistical library | |||||||
| PREV LETTER NEXT LETTER | FRAMES NO FRAMES | |||||||