The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Added generic function estimate
to retrieve estimation result for all fit functions.
Added generic function vcov
to evaluate covariance matrix of estimate for all fit functions’ result.
Added a new vignette.
Added function rBB
for simulation Brownian bridge.
Added function rMRB
for simulation moving-resting bridge.
Updated package description by adding new references.
Updated citation information.
Added print_level
to fitMRME
and fitMRH
that controls how much output is shown during the optimization process.
Added appropriate PKGNAME-package as per “Documenting packages” in R-exts.
rMM
(simulation), fitMM
(point estimator), estVarMM
(standard error).Fixed bugs in seasonal toolbox.
Updated .cpp files to adapt the update of R package Rcpp
.
Modified estVarMRME_Godambe
and estVarMRME_pBootstrap
.
Added ‘f109’ data.
smam
. So, this is why I submitted such many versions.Added moving-resting model with measurement error is modeled as Gaussian noise as fitMRME
.
Added estimator variance function for fitMRME
as estVarMRME_Godambe
and estVarMRME_pBootstrap
.
Added moving-resting-handling model with both full likelihood and composite likelihood.
Provided option to use only part of dataset to fit BMME model, moving-resting model and moving-resting-handling model (in function fitBMME
, fitMR
, and fitMRH
).
Provided tools for seasonal behavior analysis.
Parallel code is implemented for moving-resting-handling model to speed code up.
Added code for predicting state at given time point under MR model and MRH model (beta version).
Added vignette for quick start.
Redocumented whole package.
Renamed rBmme -> rBMME
, fitBmme -> fitBMME
, rMovRes -> rMR
and fitMovRes -> fitMR
.
Provided option to show simulated states in rMR
and rMRH
.
Added full likelihood based hidden Markov model
Full likelihood and composite likelihood are now done with Rcpp
Added Depends: R (>= 3.0.0).
Corrected double to void of C function pmr.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.