fun.gen.qrn

This function calls the <code>runif.sobol</code>, <code>runif.sobol.owen</code> and 
 <code>runif.halton</code> essentially from the spacefillr package.

datagen

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>.

Steve Su

GLDEX

Fitting Single and Mixture of Generalised Lambda Distributions

Martin Maechler

Juha Karvanen

Robert King

Benjamin Dean

R Core Team

fun.gen.qrn function

<dl> <dt>n</dt>
<dd>Number to generate.</dd> <dt>dimension</dt>
<dd>Number of dimensions.</dd> <dt>scrambling</dt>
<dd>seed used, or leap as in the case of 
 <code>QUnif</code>.</dd> <dt>FUN</dt>
<dd>This can be <code>"runif.sobol"</code> (default), <code>"runif.sobol.owen"</code>, <code>"runif.halton"</code> 
 or <code>"QUnif"</code>.</dd></dl>

Arguments

Author

Finds the low discrepancy quasi random numbers — fun.gen.qrn

<dl>

 <dt>n</dt>
<dd>Number to generate.</dd>

 <dt>dimension</dt>
<dd>Number of dimensions.</dd>

 <dt>scrambling</dt>
<dd>seed used, or leap as in the case of 
 <code>QUnif</code>.</dd>

 <dt>FUN</dt>
<dd>This can be <code>"runif.sobol"</code> (default), <code>"runif.sobol.owen"</code>, <code>"runif.halton"</code> 
 or <code>"QUnif"</code>.</dd>

</dl>

fun.gen.qrn: Finds the low discrepancy quasi random numbers

Description

Usage

Value

Arguments

Author

Examples