Description Usage Arguments Details Value Author(s) Source References See Also Examples
Fit of the BMT distribution to non-censored data by maximum product of spacing estimation (mpse), also called maximum spacing estimation.
1 2 3 4 |
data |
A numeric vector with the observed values for non-censored data. |
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 |
This function is not intended to be called directly but is internally
called in BMTfit
when used with the maximum product of spacing
method.
BMTfit.mpse
is based on the function mpsedist
but it
focuses on the maximum product of spacing parameter estimation for the BMT
distribution (see BMT
for details about the BMT distribution
and mpsedist
for details about maximum product of spacing fit
of univariate distributions).
BMTfit.mpse
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. |
loglik |
the log-likelihood value. |
hessian |
a symmetric matrix computed by |
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 |
Camilo Jose Torres-Jimenez [aut,cre] cjtorresj@unal.edu.co
Based on the function mpsedist
which in turn is based on
the function mledist
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.
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 BMT
for the BMT density, distribution, quantile
function and random deviates. See BMTfit.mme
,
BMTfit.qme
, BMTfit.mge
, BMTfit.mle
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"
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # (1) basic fit by maximum product of spacing estimation
set.seed(1234)
x1 <- rBMT(n=100, p3 = 0.25, p4 = 0.75)
BMTfit.mpse(x1)
# (2) how to change the optimisation method?
BMTfit.mpse(x1, optim.method="L-BFGS-B")
BMTfit.mpse(x1, custom.optim="nlminb")
# (3) estimation of the tails weights parameters of the BMT
# distribution with domain fixed at [0,1]
BMTfit.mpse(x1, start=list(p3=0.5, p4=0.5), fix.arg=list(p1=0, p2=1))
# (4) estimation of the asymmetry-steepness parameters of the BMT
# distribution with domain fixed at [0,1]
BMTfit.mpse(x1, start=list(p3=0, p4=0.5), type.p.3.4 = "a-s",
fix.arg=list(p1=0, p2=1))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.