Uses of Package
dev.nm.stat.distribution.univariate
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Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.cointegration Class Description EmpiricalDistribution An empirical cumulative probability distribution function is a cumulative probability distribution function that assigns probability 1/n at each of the n numbers in a sample.ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.distribution.univariate Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.distribution.univariate.exponentialfamily Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.evt.evd.univariate Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.hmm.mixture.distribution Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.random.rng.univariate Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.distribution.kolmogorov Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.distribution.normality Class Description EmpiricalDistribution An empirical cumulative probability distribution function is a cumulative probability distribution function that assigns probability 1/n at each of the n numbers in a sample.ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.distribution.pearson Class Description EmpiricalDistribution An empirical cumulative probability distribution function is a cumulative probability distribution function that assigns probability 1/n at each of the n numbers in a sample.ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.rank.wilcoxon Class Description ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous). -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.regression.linear.heteroskedasticity Class Description ChiSquareDistribution The Chi-square distribution is the distribution of the sum of the squares of a set of statistically independent standard Gaussian random variables. -
Classes in dev.nm.stat.distribution.univariate used by dev.nm.stat.test.timeseries.adf Class Description EmpiricalDistribution An empirical cumulative probability distribution function is a cumulative probability distribution function that assigns probability 1/n at each of the n numbers in a sample.ProbabilityDistribution A univariate probability distribution completely characterizes a random variable by stipulating the probability of each value of a random variable (when the variable is discrete), or the probability of the value falling within a particular interval (when the variable is continuous).