| BMTfit.qme {BMT} | R Documentation | 
Quantile Matching Fit of the BMT Distribution to Non-censored Data.
Description
Fit of the BMT distribution to non-censored data by quantile matching estimation (qme).
Usage
BMTfit.qme(data, probs = c(0.2, 0.4, 0.6, 0.8), qtype = 7, start = list(p3
  = 0.5, p4 = 0.5, p1 = min(data) - 0.1, p2 = max(data) + 0.1),
  fix.arg = NULL, type.p.3.4 = "t w", type.p.1.2 = "c-d",
  optim.method = "Nelder-Mead", custom.optim = NULL, silent = TRUE, ...)
Arguments
| data | A numeric vector with the observed values for non-censored data. | 
| probs | A numeric vector of the probabilities for which the quantile matching is done. The length of this vector must be equal to the number of parameters to estimate. | 
| qtype | The quantile type used by the R  | 
| start | A named list giving the initial values of parameters of the BMT 
distribution or a function of data computing initial values and returning a 
named list. (see the 'details' section of 
 | 
| fix.arg | An optional named list giving the values of fixed parameters of
the BMT distribution or a function of data computing (fixed) parameter 
values and returning a named list. Parameters with fixed value are thus NOT 
estimated. (see the 'details' section of 
 | 
| type.p.3.4 | Type of parametrization asociated to p3 and p4. "t w" means tails weights parametrization (default) and "a-s" means asymmetry-steepness parametrization. | 
| type.p.1.2 | Type of parametrization asociated to p1 and p2. "c-d" means domain parametrization (default) and "l-s" means location-scale parametrization. | 
| optim.method | 
 | 
| custom.optim | A function carrying the optimization (see the 'details' 
section of  | 
| silent | A logical to remove or show warnings when bootstraping. | 
| ... | Further arguments to be passed to generic functions or to the 
function  | 
Details
This function is not intended to be called directly but is internally
called in BMTfit when used with the quantile matching method.
BMTfit.qme is based on the function qmedist but it 
focuses on the quantile matching parameter estimation for the BMT 
distribution (see BMT for details about the BMT distribution 
and qmedist for details about quantile matching fit of 
univariate distributions).
Value
BMTfit.qme returns a list with following components,
| estimate | the parameter estimates. | 
| convergence |  an integer code for the convergence of 
 
 
 
 
 | 
| value | the value of the corresponding objective function of the estimation method at the estimate. | 
| hessian | a symmetric matrix computed by  | 
| loglik | the log-likelihood value. | 
| probs | the probability vector on which quantiles are matched. | 
| optim.function | the name of the optimization function used for maximum product of spacing. | 
| optim.method | when  | 
| fix.arg | the named list giving the values of parameters of the named 
distribution that must kept fixed rather than estimated or  | 
| fix.arg.fun | the function used to set the value of  | 
| weights | the vector of weigths used in the estimation process or 
 | 
| counts | A two-element integer vector giving the number of calls to the
log-likelihood function and its gradient respectively. This excludes those 
calls needed to compute the Hessian, if requested, and any calls to 
log-likelihood function to compute a finite-difference approximation to the 
gradient.  | 
| optim.message | A character string giving any additional information 
returned by the optimizer, or  | 
Author(s)
Camilo Jose Torres-Jimenez [aut,cre] cjtorresj@unal.edu.co
Source
Based on the function qmedist of the R package: 
fitdistrplus
Delignette-Muller ML and Dutang C (2015), fitdistrplus: An R Package for Fitting Distributions. Journal of Statistical Software, 64(4), 1-34.
References
Torres-Jimenez, C. J. (2017, September), Comparison of estimation methods for the BMT distribution. ArXiv e-prints.
Torres-Jimenez, C. J. (2018), The BMT Item Response Theory model: A new skewed distribution family with bounded domain and an IRT model based on it, PhD thesis, Doctorado en ciencias - Estadistica, Universidad Nacional de Colombia, Sede Bogota.
See Also
See BMT for the BMT density, distribution, quantile 
function and random deviates. See BMTfit.mme, 
BMTfit.mle, BMTfit.mge, 
BMTfit.mpse and BMTfit.mqde for other estimation
methods. See optim and constrOptim for 
optimization routines. See BMTfit and fitdist 
for functions that return an objetc of class "fitdist".
Examples
# (1) basic fit by quantile matching estimation
set.seed(1234)
x1 <- rBMT(n=100, p3 = 0.25, p4 = 0.75)
BMTfit.qme(x1)
# (2) changing the probability vector on which quantiles are matched
BMTfit.qme(x1, probs=c(0.1,0.3,0.5,0.75))
# (3) how to change the optimisation method?
BMTfit.qme(x1, optim.method="L-BFGS-B") 
BMTfit.qme(x1, custom.optim="nlminb")
# (4) estimation of the tails weights parameters of the BMT 
# distribution with domain fixed at [0,1]
BMTfit.qme(x1, start=list(p3=0.5, p4=0.5), 
           fix.arg=list(p1=0, p2=1), probs=c(1/3,2/3))
# (5) estimation of the asymmetry-steepness parameters of the BMT 
# distribution with domain fixed at [0,1]
BMTfit.qme(x1, start=list(p3=0, p4=0.5), type.p.3.4 = "a-s", 
           fix.arg=list(p1=0, p2=1), probs=c(1/3,2/3))