Fitting Single and Mixture of Generalised Lambda Distributions
Digit/Bit Representation of Integers in any Base
This is a collection of functions designed to implement the fitting al...
This is a collection of functions designed to find the initial values ...
Fitting mixture of generalied lambda distribtions to data using maximu...
Fitting mixture of generalied lambda distribtions to data using pariti...
Fitting mixtures of generalied lambda distribtions to data using quant...
This is a collection of functions used in the calculation of the beta ...
Finds the final fits using the maximum likelihood estimation for the b...
Finds the final fits using partition maximum likelihood estimation for...
Finds the initial values for optimisation in fitting the bimodal gener...
Check whether the RS or FMKL/FKML GLD is a valid GLD for vectors of L1...
Check whether the RS or FMKL/FKML GLD is a valid GLD for single values...
Classifies data into two groups using a clustering regime.
Compare the moments of the data and the fitted univariate generalised ...
Compare the moments of the data and the fitted univariate generalised ...
Fit RS and FMKL generalised distributions to data using discretised ap...
Fit RS and FMKL generalised distributions to data using discretised ap...
Fit data using L moment matching estimation for RS and FMKL GLD
Fit data using RS, FMKL maximum likelihood estimation and the FMKL sta...
Fit data using moment matching estimation for RS and FMKL GLD
Fit data using quantile matching estimation for RS and FMKL GLD
Compute the simulated Kolmogorov-Smirnov tests for the bimodal dataset
Compute the simulated Kolmogorov-Smirnov tests for the unimodal datase...
Diagnostic function for theoretical distribution fits through the resa...
Diagnostic function for empirical data distribution fits through the r...
Estimates the mean and variance after cutting up a vector of variable ...
Finds the low discrepancy quasi random numbers
Find the theoretical first four L moments of the generalised lambda di...
Applying functions based on an index for a matrix.
Check whether the specified GLDs cover the minimum and the maximum val...
Finds the moments of fitted mixture of generalised lambda distribution...
Calculate mean, variance, skewness and kurtosis of a numerical vector
Estimates the number of classes or bins to smooth over in the discreti...
Plotting mixture of two generalised lambda distributions on the data s...
Plotting the univariate generalised lambda distribution fits on the da...
Plotting many univariate generalised lambda distributions on one page.
Computes the raw moments of the generalised lambda distribution up to ...
Fit FMKL generalised distribution to data using discretised approach w...
Fit FMKL generalised distribution to data using discretised approach w...
Fit FMKL generalised lambda distribution to data set using L moment ma...
Fit RS generalised lambda distribution to data set using maximum likel...
Fit FMKL generalised lambda distribution to data set using maximum lik...
Fit FMKL generalised lambda distribution to data set using moment matc...
Fit FMKL generalised lambda distribution to data set using quantile ma...
Fit RS generalised distribution to data using discretised approach wit...
Fit RS generalised distribution to data using discretised approach wit...
Fit RS generalised lambda distribution to data set using L moment matc...
Fit RS generalised lambda distribution to data set using maximum likel...
Fit RS generalised lambda distribution to data set using maximum likel...
Fit RS generalised lambda distribution to data set using moment matchi...
Fit RS generalised lambda distribution to data set using quantile matc...
Simulate a mixture of two generalised lambda distributions.
Calculates the theoretical mean, variance, skewness and kurtosis for m...
Find the theoretical first four moments of the generalised lambda dist...
Determine which values are zero.
Returns a vector after removing all the zeros.
Checks whether the parameters provided constitute a valid generalised ...
Checks whether the parameters provided constitute a valid generalised ...
This package fits RS and FMKL generalised lambda distributions using v...
The Generalised Lambda Distribution Family
This is a collection of functions designed to implement the basic GLD ...
Histogram with exact number of bins specified by the user
Returns a logical vecto, TRUE if the value is Inf or -Inf.
Returns a logical vector TRUE, if the value is not Inf or -Inf.
Kolmogorov-Smirnov test
L-moments
This is a collection of functions used in the optimisation processes f...
An alternative to the normal pretty function in R.
Do a quantile plot on the bimodal distribution fits.
Do a quantile plot on the univariate distribution fits.
Quasi Randum Numbers via Halton Sequences
This is a collection of functions designed to find the initial values ...
Compute skewness and kurtosis statistics
Carry out the ``starship'' estimation method for the generalised lambd...
Objective function that is minimised in starship estimation method
Carry out the ``starship'' estimation method for the generalised lambd...
Trimmed L-moments
Determine Missing Values
The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution. References include the following: Karvanen and Nuutinen (2008) "Characterizing the generalized lambda distribution by L-moments" <doi:10.1016/j.csda.2007.06.021>, King and MacGillivray (1999) "A starship method for fitting the generalised lambda distributions" <doi:10.1111/1467-842X.00089>, Su (2005) "A Discretized Approach to Flexibly Fit Generalized Lambda Distributions to Data" <doi:10.22237/jmasm/1130803560>, Su (2007) "Nmerical Maximum Log Likelihood Estimation for Generalized Lambda Distributions" <doi:10.1016/j.csda.2006.06.008>, Su (2007) "Fitting Single and Mixture of Generalized Lambda Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R" <doi:10.18637/jss.v021.i09>, Su (2009) "Confidence Intervals for Quantiles Using Generalized Lambda Distributions" <doi:10.1016/j.csda.2009.02.014>, Su (2010) "Chapter 14: Fitting GLDs and Mixture of GLDs to Data using Quantile Matching Method" <doi:10.1201/b10159>, Su (2010) "Chapter 15: Fitting GLD to data using GLDEX 1.0.4 in R" <doi:10.1201/b10159>, Su (2015) "Flexible Parametric Quantile Regression Model" <doi:10.1007/s11222-014-9457-1>, Su (2021) "Flexible parametric accelerated failure time model"<doi:10.1080/10543406.2021.1934854>.