Package index • univariateML

All functions

dml() pml() qml() rml(): Maximum likelihood estimated distribution

ppmlplot() ppmlline() ppmlpoints() qqmlplot() qqmlline() qqmlpoints(): Probability Plots Using Maximum Likelihood Estimates

abalone: Abalone data

bootstrapml(): Parametric Bootstrap on Distributions Fitted with Maximum Likelihood

confint(<univariateML>): Confidence Intervals for Maximum Likelihood Estimates

corbet: Frequencies of butterflies collected in Malaya

egypt: Mortality data from ancient Egypt

get_start(): Returns appropriate starting value

inverse_digamma(): Inverse digamma function

mlbeta(): Beta distribution maximum likelihood estimation

mlbetapr(): Beta prime distribution maximum likelihood estimation

mlbinom(): Binomial distribution maximum likelihood estimation

mlburr(): Burr distribution maximum likelihood estimation

mlcauchy(): Cauchy distribution maximum likelihood estimation

mldunif(): Discrete uniform distribution maximum likelihood estimation

mlexp(): Exponential distribution maximum likelihood estimation

mlfatigue(): Gamma distribution maximum likelihood estimation

mlgamma(): Gamma distribution maximum likelihood estimation

mlged(): Generalized Error distribution maximum likelihood estimation

mlgeom(): Geometric distribution maximum likelihood estimation

mlgompertz(): Gompertz distribution maximum likelihood estimation

mlgumbel(): Gumbel distribution maximum likelihood estimation

mlinvburr(): Inverse Burr distribution maximum likelihood estimation

mlinvgamma(): Inverse Gamma distribution maximum likelihood estimation

mlinvgauss(): Inverse Gaussian (Wald) maximum likelihood estimation

mlinvweibull(): Inverse Weibull distribution maximum likelihood estimation

mlkumar(): Kumaraswamy distribution maximum likelihood estimation

mllaplace(): Laplace distribution maximum likelihood estimation

mllgamma(): Log-gamma distribution maximum likelihood estimation

mllgser(): Logarithmic series distribution maximum likelihood estimation

mlllogis(): Log-logistic distribution maximum likelihood estimation

mllnorm(): Log-normal distribution maximum likelihood estimation

mllogis(): Logistic distribution maximum likelihood estimation

mllogitnorm(): Logit-Normal distribution maximum likelihood estimation

mllomax(): Lomax distribution maximum likelihood estimation

mlnaka(): Nakagami distribution maximum likelihood estimation

mlnbinom(): Negative binomial distribution maximum likelihood estimation

mlnorm(): Normal distribution maximum likelihood estimation

mlparalogis(): Paralogistic distribution maximum likelihood estimation

mlpareto(): Pareto distribution maximum likelihood estimation

mlpois(): Poisson distribution maximum likelihood estimation

mlpower(): Power distribution maximum likelihood estimation

mlrayleigh(): Rayleigh distribution maximum likelihood estimation

mlsged(): Skew Generalized Error distribution maximum likelihood estimation

mlsnorm(): Skew Normal distribution maximum likelihood estimation

mlsstd(): Skew Student t-distribution maximum likelihood estimation

mlstd(): Student-t distribution maximum likelihood estimation

mlunif(): Uniform distribution maximum likelihood estimation

mlweibull(): Weibull distribution maximum likelihood estimation

mlzip(): Zero-inflated Poisson distribution maximum likelihood estimation

mlzipf(): Zipf distribution maximum likelihood estimation

model_select(): Fit multiple models and select the best fit

plot(<univariateML>) lines(<univariateML>) points(<univariateML>): Plot, Lines and Points Methods for Maximum Likelihood Estimates

univariateML univariateML-package: univariateML

univariateML_construct(): Construct univariateML object.

univariateML_metadata: Metadata for univariateML models.

univariateML_models: Implemented models