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#Com.numericalmethod.suanshu.stats.evt.evd.univariate Classes and Interfaces - 32 results found.
| Name | Description | Type | Package | Framework |
| ACERAnalysis | Average Conditional Exceedance Rate (ACER) method is for estimating the cdf of the maxima (M) distribution from observations. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERAnalysis .Result | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu | |
| ACERByCounting | Estimate epsilons by counting conditional exceedances from the observations. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| ACERConfidenceInterval | Using the given (estimated) ACER function as the mean, find the ACER parameters at the lower and upper bounds of the estimated confidence interval of ACER values. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERFunction | The ACER (Average Conditional Exceedance Rate) function (epsilon_k(eta)) approximates the epsilon_k(eta) = Pr(X_k > eta | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERFunction .ACERParameter | Parameters for ACERFunction. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERInverseFunction | The inverse of the ACER function. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERLogFunction | The ACER function in log scale (base e), i. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERReturnLevel | Given an ACER function, compute the return level (eta) for a given return period (R). | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| ACERUtils | Utility functions used in ACER empirical analysis. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| ConfidenceInterval | This class stores information for a list of confidence intervals, with the same confidence level. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting | SuanShu |
| EmpiricalACER | This class contains empirical ACER (hat{epsilon_k}(eta_i)) values and other related statistics estimated from observations. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| EmpiricalACEREstimation | This class estimates empirical ACER values from the given observations. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| EmpiricalACERStatistics | This class contains the computed statistics of the estimated ACERs. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| EpsilonStatisticsCalculator | Compute statistics: mean, confidence interval of estimated ACER values (epsilon_k(eta_i)). | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer.empirical | SuanShu |
| FrechetDistribution | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu | |
| GeneralizedEVD | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu | |
| GeneralizedParetoDistribution | Generalized Pareto distribution (GPD) is used for modeling exceedances over (or shortfalls below) a threshold. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| GEVFittingByMaximumLikelihood | Estimate the GeneralizedEVD parameter from the observations by maximum likelihood approach. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting | SuanShu |
| GumbelDistribution | The Gumbel distribution is a special case (Type I) of the generalized extreme value distribution, The cumulative distribution function is | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| InverseTransformSamplingEVDRNG | Generate random numbers according to a given univariate extreme value distribution, by inverse transform sampling. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.rng | SuanShu |
| LinearFit | Find the parameters for the ACER function from the given empirical epsilon, using OLS regression on the logarithm of the values. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| MaximaDistribution | The distribution of (M), where (M=max(x_1,x_2,. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| MaximumLikelihoodFitting | This interface defines model fitting by maximum likelihood algorithm. | Interface | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting | SuanShu |
| MinimaDistribution | The distribution of (M), where (M=min(x_1,x_2,. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| NonlinearFit | Fit log-ACER function by sequential quadratic programming (SQP) minimization (of weighted RSS), using LinearFit's solution as the initial guess. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu |
| NonlinearFit .Result | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.acer | SuanShu | |
| OrderStatisticsDistribution | The asymptotic nondegenerate distributions of the r-th smallest (largest) order statistic. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| PeaksOverThreshold | Peaks Over Threshold (POT) method estimates the parameters for generalized Pareto distribution (GPD) using maximum likelihood on the observations that are over a given threshold. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.pot | SuanShu |
| PeaksOverThresholdOnClusters | Similar to POT, but only use the peak observations in clusters for the parametric estimation. | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate.fitting.pot | SuanShu |
| ReversedWeibullDistribution | The Reversed Weibull distribution is a special case (Type III) of the generalized extreme value distribution, with (xi<0). | Class | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |
| UnivariateEVD | Distribution of extreme values (e. | Interface | com.numericalmethod.suanshu.stats.evt.evd.univariate | SuanShu |