BLRPM.est {BLRPM}  R Documentation 
BLRPM.est
estimates the five BartlettLewis rectangular pulse model parameters lambda,gamma,beta,eta,mux
for a given time series data
. At first the time series statistics at given accumulation levels acc.vals
are calculated. These statistics are given over to the parameter estimation algorithm together with
parameter starting values par
. An objective function O.Fun
can be specified, default is BLRPM.OF
.
In addition the weights for different statistics and accumulation levels weights.mean, weights.var, weights.cov, weights.pz
can be specified. For the BLRPM objective function the user can select the measure of distance between observation
and model with OF
: =1 quadratic, =2: quad extended, =3: absolute, =4: abs extended.
A scale
parameter controls different cases in the objective function for differences in the scale of duration
parameters gamma and eta.
If a debugging is wished, debug
can be set to TRUE
and a log file is created in working directory.
Several optim
parameters can be also defined. For specifics see ?optim
.
BLRPM.est(RR,acc.vals,pars.in,O.Fun,
weights.mean,weights.var,weights.cov,weights.pz,OF,debug,
scale,method,lower,upper,use.log,maxit,ndeps,trace)
RR 

acc.vals 

pars.in 

O.Fun 

weights.mean 

weights.var 

weights.cov 

weights.pz 

OF 

debug 
set 
scale 

method 

lower 

upper 

use.log 

maxit 

ndeps 

trace 

$est returns vector
of estimated parameters lambda,gamma,beta,eta,mux
$conv returns value
of convergence of optimization, see optim
for details
$mess returns character
message about optimization if using "LBFGSB" method
$Z returns value
of objective function for estimated parameters
Christoph Ritschel christoph.ritschel@met.fuberlin.de
t.sim=240
lambda < 4/240
gamma < 1/10
beta < 0.3
eta < 2
mux < 4
pars < c(lambda,gamma,beta,eta,mux)
sim < BLRPM.sim(lambda,gamma,beta,eta,mux,t.sim)
est < BLRPM.est(sim$RR,pars.in=pars,method="BFGS",use.log=TRUE)