ctmm 1.2.0 (2023-09-22)
- new function names: cde() and encounter() replacing encounter() and
rates()
- new functions rsf.select(), intensity()
- new functions sdm.fit(), sdm.select()
- new function writeVector(), depreciating function
writeShapefile()
- new function funnel() for funnel plots
- new function midpoint()
- new population covariance models and improved model selection in
mean.ctmm()
- new argument ‘sqrt’ in distance()
- new argument ‘dt.hot’ in as.telemetry()
- new argument ‘variable’ in Log()
- new argument ‘compute’ in ctmm.loglike()
- new argument ‘t’ in proximity()
- as.telemetry() now supports GBIF format data
- as.telemetry() datum argument now works on UTM import, and is no
longer to a be a complete PROJ string
- as.telemetry() timeformat=‘auto’ now default
- as.telemetry(), plot.telemetry(), rsf.fit() updated from sp to sf
transforms
- distance() can now take location arguments
- plot.telemetry() col.DF & col.level arguments can now be color()
lists
- suitability() now produces a raster stack corresponding to the
CIs
- suitability() on population RSFs now outputs the population
suitability
- suitability() extrapolation disabled
- bugfix in tbind for conflicting location classes
- bugfix in suitability()
- bugfix in distance() method=“Euclidean”, debias=TRUE
- bugfix in rates() debias=TRUE
- bugfix in summary() of population mean location DOF
- bugfix in distances() for 0/0
- bugfix in UD polygon export for tiny areas
- as.telemetry() UTM import updated to new PROJ specification
- mean.ctmm() improved convergence, numerical stability, and
covariance selection
- meta() stability improvements for tiny DOF estimates, and OUf
support
- overlap() and meta() can now extract object names
- pkde(…) -> akde(…) -> bandwidth(…) -> mean(…) arguments now
passed
- rsf.fit() AICc formula improved
ctmm 1.1.0 (2022-11-03)
- new function pkde() for population kernel density estimates
- new functions difference(), distances(), proximity() for estimating
distances between individuals
- new functions Log(), Exp() to log transform parameter estimates and
their uncertainties for meta-analytic regression
- new functions dimfig(), sigfig() to represent quantities with
concise units and significant digits
- new argument ‘sample’ in mean()
- new argument ‘interpolate’ in rsf.fit()
- new arguments ‘xlim’, ‘ylim’ to plot.outlie()
- numerical stability improvements in rsf.fit optimization and hessian
calculations
- numerical convergence improvements in location error fitting
- numerical convergence improvements in AKDE weight optimization
- plot.telemetry() can now subset and reproject rasters
- bugfix in sp::polygon derived areas (used since v1.0.0 for summary,
plot, meta)
- bugfix in agde(), suitability(), akde() when reprojecting onto the
same raster
- bugfix in mean() when averaging isotropic and anisotropic models
together
- bugfix in speeds() without telemetry object
- bugfix in cluster() with 0/0 bias correction error
- bugfix in occurrence() with multiple error classes
- bugfix in chi dof computation
- bugfix in outlie() for error ellipses
- summary() now works on mean.ctmm() outputs from different input
model structures (OUF & OUO)
- fixed log-chi^2 bias correction in mean.ctmm()
ctmm 1.0.0 (2022-07-07)
- new function rsf.fit() to fit integrated resource selection
functions (iRSFs) with autocorrelation-adjusted weighted likelihood
- new function mean.ctmm() to calculate population average movement
models
- new function revisitation() to calculate the distribution of
revisitations
- new function npr() to calculate non-parametric spatial
regressions
- new function agde() to calculate autocorrelated Gaussian
distribution estimates, with RSF support
- new function suitability() to calculate suitability rasters from RSF
fit objects
- new function rates() to calculate relative encounter rates
- new function dt.plot() to inspect sampling intervals
- akde() and occurrence() now support RSF-informed kernels and
boundary-respecting kernels
- summary.ctmm() now outputs diffusion rate estimates
- new argument variable for meta() to estimate population diffusion
rates, mean speeds, and autocorrelation timescales
- new arguments R and SP in plot.telemetry() and plot.UD() for
plotting raster and shapefile base layers
- new option method=“Encounter” in overlap()
- mean.UD() now propagates uncertainties
- mean.UD() now functions on occurrence distributions
- new convex argument to UD summary(), plot(), and export
functions
- plot() and raster() now work on 3D UDs
- plot.outlie() now works on lists of outlie objects
- speed() output now includes DOF estimate for use with meta()
- tbind() now works correctly with different projections and
calibrations
- %#% unit conversion operator can now interpret products and
ratios
- summary() timescale confidence intervals are now gamma/inverse-gamma
more inline with meta()
- progress bar added to optimizer() when trace=1
- bugfix in IID area CIs
- bugfix in ctmm.loglike() when fitting multiple error classes, where
some are zero
- bugfix in ctmm.boot() when bias estimate exceeds variance
parameter
- bugfixes in 3D akde()
- bugfix in time gridding code when dt is coarse
- bugfix in SpatialPoints.telemetry for single individuals
ctmm 0.6.1 (2021-07-26)
- ctmm.fit() can now fit multiple UERE parameters and update uncertain
calibration parameter estimates
- new function cluster()
- new function video()
- new function as.sf()
- new function tbind()
- new argument VMM in simulate(), predict()
- new argument timeformat=“auto” in as.telemetry()
- new argument verbose in meta()
- uere()<- can now assign posterior/updated error estimates from
ctmm model objects
- bugfix in ctmm.loglike() for circle!=0 and REML
- bugfixes in optimzer()
- bugfix in ctmm.fit() for 1D processes
- bugfix in variogram.fit() for 1D processes
- bugfixes in simulate(), predict for 1D processes
- bugfix in ctmm.fit() with zero variance models
- bugfix in meta() colors when sort=TRUE
- bugfixes in ctmm.guess(), ctmm.fit(), speed() for tiny amounts of
data
- bugfixes in occurrence(), Kalman smoother for IOU process
- ctmm.select() now stores IC and MSPE information for summary()
- extent objects now include missing columns
- extent object longitudes can now cross the international date
line
ctmm 0.6.0 (2021-01-08)
- new function meta() for meta-analysis of home-range areas
- new function encounter() for the conditional distribution of
encounters (CDE)
- new function distance() to calculate square Bhattacharyya,
Mahalanobis, and Euclidean distances
- new function compass() to plot a north-pointing compass
- new argument ‘t’ in speed()
- new argument ‘axes’ in outlie()
- as.telemetry() now accepts most tibble objects
- akde() on multiple individuals is now more memory efficient
- bugfix in ctmm.fit() for IOU model
- bugfix in occurrence() with repeated timestamps
- bugfix in summary.ctmm() rowname droped for single parameter
CIs
- bugfix in outlie() with list input
- bugfixes in plot.outlie with zero error
- bugfix in variogram() with res>1 and CI=“Gauss”
- bugfix in ctmm.select() if stepping OU->OUf->OUF
- bugfix in as.telemetry() for Move objects with empty idData
slot
- bugfix in as.telemetry(), median() when importing single location
estimate
- bugfix in plot.telemery() with add=TRUE and non-SI units
- bugfix in speed() for ctmm objects (no data), where CIs were
incorrect
- bugfix in median() with >=50% repeating observations
- bugfix in summary() for periodic models with tau[velocity]==0
- bugfix in occurrence() for PDclamp() error
- bugfix in ctmm.select() giving incorrect model names when run
indirectly
- bugfix in occurrence() with IID autocorrelation model
- workaround in export functions where sp objects change
timezones
- workaround in as.telemetry() when Move idData() names are
dropped
- workaround in plot.UD() when image() has alpha overflow
- improvements to akde(), occurrence() grid argument when
incomplete
- improvements to overlap() Wishart approximation in bias
correction
- improvements to cleave()
ctmm 0.5.10 (2020-05-04)
- as.telemetry() location class code improved
- as.telemetry() message for marked outliers
- jaguar data in sync with ctmmweb
ctmm 0.5.9 (2020-03-23)
- new argument CI=“Gauss” in variogram()
- new argument weights in mean.UD()
- new argument datum in as.telemetry() – input and ouput datums can
now differ
- new data ‘jaguar’
- bugfix in ctmm.select() for infinte loop
- improvements in ctmm.select, ctmm.loglike for collapsing
variance/error estimates
- rewrite of optimizer’s line search to be more exact &
reliable
- improvements in optimizer for degenerate likelihood surfaces
- improvements in optimization for bad covariance estimates—fit object
structure changed
- bugfix in uere.fit with multiple location classes in different
orders
- bugfix in speed when fast=FALSE and sampled models lose
features
- bugfix in IID pREML CIs
- bugfix in ctmm.guess with large errors causing eigen() to fail
- bugfix in optimizer expansion search step size not increasing
- bugfix in as.telemetry() – MoveStack objects are given a common
projection if not projected
ctmm 0.5.8 (2019-12-09)
- improvements to ctmm.select() stepwise selection, especially with
error and/or circulation
- improvements to ctmm.fit() for nearly linear home ranges
- improvements to %#% operator – units of speed supported
- bugfix in ctmm.loglike() for BM/IOU models with error
- new argument units in plot.outlie()
- new options(time.units=‘mean’) and options(time.units=‘calendar’)
for %#% operator and display units
- ctmm.select() no longer warns when model features are not supported
(ctmm.fit does)
- compatibility fix for R version 4
ctmm 0.5.7 (2019-10-06)
- new function optimizer()
- new function SpatialPolygonsDataFrame.telemetry() for location
estimate error circles/ellipses
- ‘pNewton’ now the default optimization method
- ‘pHREML’ now the default estimator & all CI names updated
- grid argument now supported in akde and occurrence methods
- outlie() output now includes CIs with plot method
- error-adjusted variogram implemented when fast=FALSE
- LOOCV now supported in ctmm.select(), summary()
- new buffer argument in occurrence()
- head(), tail() methods for telemetry objects
- str() method for ctmm objects
- new data object ‘pelican’
- SpatialPointsDataFrame now includes timestamp
- uere(data) <- numeric now overrides all location classes
- improved support for ARGOS-GPS hybrid data
- missing DOP values now correctly treated as separate location
class
- bugfix in conditional simulations with dt argument
- bugfix in plot.UD gridlines
- bugfix in as.telemetry timeout argument when datasets lack timed-out
values
- stability fixes in ctmm.fit() for BM/IOU models
- further stability enhancements in ctmm.loglike() and optimizer
- bugfix in simultaneously fit RMS UERE CIs
- AICc formulas fixed for tiny n
- reduced Z^2 now exactly normalized in UERE objects
- minor enhancements to cleave() function
- as.telemetry() no longer automatically calibrates e-obs errors
(inconsistent with newer devices)
- as.telemetry() no longer complains on reverse-time-ordered
files
ctmm 0.5.6 (2019-05-14)
- new functions lasso, marquee, and cleave
- new functions annotate and color
- summary can now compare joint UERE objects to lists of
individualized UERE objects
- support for UTM locations in as.telemetry
- support for GPS-ARGOS hybrid data in as.telemetry &
uere.fit
- new plot option ext for extent objects
- increased numerical precision in ctmm.loglike for 0 < dt <<
tau, including the limit OU/OUF -> BM/OU
- BM/IOU model likelihoods are now exact limits of OU/OUF likelihoods
modulo a constant
- covariance matrices can now take arbitrary eccentricty and
scale
- ctmm.boot new argument iterate=FALSE and bugfixes for
iterate=TRUE
- ctmm.boot now debiases the covariance matrix directly
(linearly)
- occurrence default dt.max & cor.min arguments now tighter
- periodogram functionality restored for one-dimensional data
- bugfix in IID ctmm.fit with elliptical errors
- bugfix in occurrence when projection origin is far from the mean
location
- bugfix in akde.list where location errors were not smoothed
- bugfix in ctmm.guess/variogram.fit for BM/IOU models
- bugfix in speed for IOU models
- e-obs calibration cross checked and fixed
- ctmm.loglike now returns -Inf when movement and error variance are
zero
- stability improvements to base R optimizer usage
- bugfix in mark.rm argument of as.telemetry
- cores option added to ctmm.select
- only physical cores now counted by cores arguments
- cores option now used in Windows when appropriate
- improvements to speed, speeds, ctmm.select for short tracks of
data
ctmm 0.5.5 (2019-02-11)
- bugfix in summary where timescale CIs were always (0,Inf)
- ctmm.select default now level=1
- summary on UERE lists now works with more than one axis
- R dependency increased to >=3.5 for parallel functions
ctmm 0.5.4 (2019-02-07)
- bugfix in ctmm.select where OU was not considered over the new
OUO/OUf models introduced in v0.5.3
- bugfix in ctmm.boot for heteroskedastic errors
- multiplicative option depreciated from ctmm.boot
ctmm 0.5.3 (2019-01-29)
- oscillatory (and critically damped) OUO/OUf models now supported,
starting with omega option of ctmm()
- summary() now works on lists of UERE objects for error model
selection
- MSPE slots & arguments restructured and fully utilized in both
summary and ctmm.select
- new method speeds() for estimating instantaneous speeds
- speed() more efficient on very coarse data, slightly improved
CIs
- new complete argument in simulate() and predict() to calculate
timestamps and geographic coordinates
- now avoiding fastPOSIXct timezone and epoch issues in
as.telemetry
- outlie() now works on lists of telemetry objects
- bugfixes in overlap() CIs
- overlap() now robust to bad model fits
- new as.telemetry() argument mark.rm to delete marked outliers
- bugfix in predict() & occurrence() where eccentricity was
dropped from covariances
- projection information in Move & MoveStack objects now preserved
if possible
- identities preserved with newer MoveStack objects
- ctmm.boot() better handles parameter estimation near boundaries
- e-obs data with missing error/speed/altitude now importing correctly
in as.telemetry
- correlogram plots now cap estimates to appropriate range
- beta optimizer now more aggressive in searching along
boundaries
- bugfix in ctmm.fit with duplicate timestamps and IID processes
without error
- bugfix in ctmm.select with pREML & error
- summary() on telemetry lists no longer fails on length-1
timeseries
- years updated to tropical years and calendar days updated to stellar
days
ctmm 0.5.2 (2018-09-10)
- location classes (multiple UEREs) now supported by uere.fit() and
uere()<-
- uere() forked into separate uere() and uere.fit() methods
- AICc slot included in UERE objects for error model selection
- overlap() telemetry and CTMM arguments depreciated
- fixed bug in as.telemetry() when importing ARGOS error ellipses
- e-obs error calibration updated
- numerical stability increased in ctmm.fit when distance scales are
extreme
ctmm 0.5.1 (2018-08-06)
- Units of measurement down to microns and microseconds now
supported
- ctmm.select() now builds up autocovariance features stepwise to help
with fit convergence
- residuals() can now be calculated from (calibrated) calibration
data—diagnostic argument removed from uere()
- summary.ctmm() now returns DOF[speed] information on
individuals
- MSPE of ctmm objects was previously w.r.t. in-sample times and is
now time averaged
- summary.list.ctmm() now returns MSPE when useful
- new speed() argument robust for coarse data
- options multiplicative & robust added to ctmm.boot to help with
parameters near boundaries
- E-OBS errors adjusted by empirical results of Scott LaPoint’s
calibration data
- Telonics Gen4 errors estimates imported with results of Patricia
Medici’s calibration data — Quick Fixes not yet fully supported
- fixed critical bug in speed()
- fixed bug in as.telemetry with projection argument
- fixed bugs in ctmm.loglike when !isotropic && error
&& circle
- fixed bug in emulate when fast=FALSE and error=TRUE
- fixed bug in new variogram error calculations (v0.5.0) used for
plotting
- simultaneously fitted UERE’s from ctmm slot “error” can now be
assigned to data for plotting
ctmm 0.5.0 (2018-05-15)
- Extensive re-write of the Kalman filter & smoother, now
supporting an arbitrary number of spatial dimensions, necessary for
ARGOS error ellipse support. (Previously, all multi-dimensional problems
were transformed into multiple one-dimensional problems.) Many new
models will be supported going forward, based on the v0.5.0 code.
- telemetry error vignette “error”
- ARGOS error ellipse support in ctmm.fit() and simulate()
- plotted variogram errors now estimated from HDOP and no longer
assumed to be homoskedastic
- as.telemetry() default projections now use robust ellipsoidal
statistics
- new median.telemetry() method for help with projecting data
- (anisotropic & circulation & error) models now exact with 2D
Kalman filter & smoother
- simulate() & predict() velocities now correct with
mean=“periodic”
- units argument in speed()
- REML and related methods fixed from 0.4.X 1/2 bug
- ctmm.loglike COV[mu] bugfix for circular error & elliptical
movement
- summary() rotation % bugfix with circle=TRUE
- parameter boundary bugfix in ctmm.fit() and ctmm.loglike()
- fixed bandwidth() bug when weights=TRUE on IID process
- variogram.fit() manipulate more appropriate with calibrated
errors
- fixed bug in plot.variogram for isotropic model fits
- fixed bug in ctmm.fit with fitted errors and any(diff(t)==0)
- fixed bug in plot.variogram() from stats::qchisq() with
k<<1
ctmm 0.4.2 (2018-02-12)
- new speed() method
- new ctmm.boot() method
- new outlie() method
- new export functionality for telemetry class
- overlap debias=TRUE option (approximate)
- pHREML, pREML, HREML ctmm.fit methods implemented and
documented
- IID pREML & REML AICc values implemented
- MSPE values implemented
- new uere()<- assignment method
- velocity esimtates now included in predict() [fitting one model to
multiple behaviors can result in wildly optimistic confidence
intervals]
- velocities now included in simulate()
- simulate precompute option
- as.telemetry drop=TRUE option
- as.telemetry will no longer drop individuals with missing data
columns
- as.telemetry will try to approximate DOP values
- as.telemetry imports velocity vectors
- as.telemetry default projection orientation now robust with
GmedianCOV
- plot.UD resolution grid less obnoxious, NA/FALSE contour label
option
- plot.telemetry error=0:3 options for data with recorded error
circles/ellipses
- plot.telemetry velocity=TRUE option for data with recorded
velocities
- plot.variogram bugfixes with telemetry errors
- fixed AIC bug in new parameterization code (0.4.0-0.4.1) where
isotropic=TRUE model would never be selected
- fixed rare endless loop in akde/bandwidth with weights=TRUE
- outlier removed from buffalo$Cilla
ctmm 0.4.1 (2017-08-30)
- projection method for ctmm objects
ctmm 0.4.0 (2017-08-29)
- periodigram vignette
- new utility function %#% for unit conversions
- new model-fit sampling function “emulate”
- summary now works on lists of telemetry objects
- new extent method for variogram objects
- bugfixes in plot.variogram with fit UERE, tau==0
- bugfixes with ctmm.fit/select/summary near boundaries
- resetting Polak–Ribiere formula in weighted AKDE conjugate gradient
routine
- read.table fallback in as.telmetry
- R 3.4 compatibility fixes
- various improvements to plot.variogram
- plot.UD & export can now accept multiple level.UD values
- increased numerical precision in ctmm.loglike
- SI speeds & diffusion fixed with units=FALSE
ctmm 0.3.6 (2017-04-23)
- AICc formulas updated from univariate to multivariate
- ctmm.select more aggressive on small sample sizes where AICc
>> AIC
- new residuals and correlogram functions
- ctmm.fit now has unified options controling optimization &
differentiation
- ctmm.fit Hessian and pREML calculations 2x faster
- new writeRaster method for UD objects
- better UD plot boxes with new extent methods
- variogram fast=TRUE less biased for irregular data with new res>1
option
- variogram fast=FALSE more robust to irregularity
- akde() can now handle duplicate times (with an error model)
- plot.variogram bugfix for fixed error models [still not quite
correct]
- Column name preferences in as.telemetry
- as.telemetry faster with fread & fastPOSIXct
- new trace option for ctmm.fit
- new labels option for plot.UD
- more robust CIs for pREML, REML
- chi-square CIs (area, semi-variance, etc.) more robust when
DOF<1
ctmm 0.3.5 (2017-02-01)
- added a FAQ page to the documentation help(“ctmm-FAQ”)
- bugfix in occurrence method for BM & IOU models
- unit conversion can now be disabled in summary with units=FALSE
argument
- added trace option to ctmm.select & bandwidth/akde
- improved telemetry error support in summary.ctmm and
plot.variogram
- as.telemetry more robust to alternative column label
capitalizations
- ctmm.loglike & ctmm.fit more robust when tau_velocity ~
tau_position
- Kalman filter & smoother upgraded to Joseph form covariance
updates
ctmm 0.3.4 (2016-11-28)
- weighted AKDE implemented, fast option, covered in vignette
- overlap arguments & ouput changed/generalized
- method akde.bandwidth renamed to bandwidth inline with S3
standards
- predict now returns covariance estimates
- occurrence distributions now exportable
- AKDE overlap bugfixes
- summary.ctmm now returns correct RMS speed
- bugfix for eccentricity errors
- variogram CIs fixed for odd dimensions
- variogram.fit can now accept OU models
- periodogram rare index bugfix
- fixed missing lag in dt-argumented variogram
- as.telemetry column identification more robust
- as.telemetry defined for MoveStack objects
ctmm 0.3.3 (2016-09-05)
- improved import of ‘move’ objects
- preliminary 3D AKDE support, debiased
- new method predict for ctmm objects
- akde now supports smoothing errors
- variogram.fit and plot.variogram now support telemetry error
- UERE fitting now possible simultaneous with tracking data
- tag.local.identifier now used as backup to
individual.local.identifier in as.telemetry
- multiple bug fixes in uere
- res.space fixed in occurrence
ctmm 0.3.2 (2016-05-12)
- new function overlap for stationary Gaussian distributions and
KDEs
- new function uere calculates UERE from calibration data
- akde debias argument removes most bias from area estimtes, now
default
- akde CIs further improved
- variogram, periodogram generalized to arbitrary dimensions
- periodic mean function option for ctmm, ctmm.fit, ctmm.select,
plot.variogram, summary (not yet documented)
- new method residuals for ctmm objects
- ctmm.select now only considers likely model modifications
- DOFs now returned in summary
- new methods [.telemetry, [.variogram, [.periodogram,
subset.periodogram
- methods for zoom, raster, writeShapefile now properly assigned to
generics
- new plot.periodogram option max
- new periodogram option res.time (with Lagrange interpolation). Old
option res renamed to res.freq.
- akde res argument is now relative to the bandwidth
- occurrence res.space argument is now relative to the average
diffusion
- plot.telemetry with data error now uses level.UD for error radius
instead of one standard deviation
- gridding function for fast=TRUE variogram and periodogram now always
fast
- bad location removed from buffalo “Pepper”
ctmm 0.3.1 (2016-02-23)
- variogram.fit now stores global variables of any name
- variogram.fit sliders now use pretty units
- variogram.fit range argument depreciated in favor of a more general
CTMM prototype argument
- akde UD CIs significantly improved for high quality datasets
- akde bugfix: subscript out of bounds
- circulatory model introduced via circle ctmm argument
- oscillatory CPF model introduced via CPF ctmm argument
- as.telemetry now imports GPS.HDOP columns with a UERE argument
- summary now works on arbitrary lists of ctmm objects
- ctmm.fit now tries to make sense of ML parameters that lie on
boundaries
- occurrence() now works when some timesteps are tiny
ctmm 0.3.0 (2015-11-26)
- new function “occurrence” to estimate occurrence distributions
- “akde” & “occurrence” class objects generalized to “UD”
class
- alpha & alpha.HR arguments simplified and generalized to level
& level.UD
- AKDE= and .HR= arguments generalized to UD= and .UD=
- new basic telemetry error functionality in ctmm, ctmm.fit
- new function ctmm.select
- new methods subset.telemetry and subset.variogram
- fixed a bug in the uncertainty report of uncorrelated processes
- ctmm.fit is now much faster by specifying a reasonable parscale for
optim
- ctmm.fit now has a backup for when Brent fails
ctmm 0.2.9 (2015-10-13)
- fixed a rare condition in ctmm.fit where solve would fail on
correlated errors
- multiscale variogram and mean variogram example in vignette
- new data example Mongolian gazelle
- new fast option for periodogram
- improvements in plot.periodogram
- bugfix in as.telemetry for numeric indentifiers
- bugfix in dt array option of variogram
- new resolution option and better estimation algorithms in akde
- alpha, alpha.HR, res arguments made consistent across all
functions
ctmm 0.2.8 (2015-08-25)
- efficiency gains in as.telemetry with multiple animals
- bugfix in plot.telemetry for multiple Gaussian PDFs
- bugfix in variogram for rare condition when fast=TRUE
ctmm 0.2.7 (2015-07-27)
- CRAN check compliance achieved.
- all methods (plot, mean, summary, simulate) can and must be run
without class extensions
- argument names no longer clash with function names and are more
explicit about their object class
ctmm 0.2.6 (2015-07-17)
ctmm 0.2.5 (2015-07-14)
- IOU bug fixes in ctmm.fit and plot.variogram
ctmm 0.2.4 (2015-06-28)
- cleaned up and labeled tau parameter arrays
- implemented Workaround for when subset demotes S4 objects to S3
objects
- plot.telemetry now enforces asp=1 even with xlim/ylim arguments
ctmm 0.2.3 (2015-06-19)
- new function summary.telemetry
- bugfix in as.telemetry for data$t
- bugfix in ctmm.loglike for some cases with numeric underflow
- periodogram and plot.periodogram can now check for spurious
periodicities
- minimal support for BM and IOU motion
ctmm 0.2.2 (2015-05-21)
- new functions periodogram, plot.periodogram
ctmm 0.2.1 (2015-05-08)
- new function SpatialPoints.telemetry returns SpatialPoints object
from telemetry data
- new function SpatialPolygonsDataFrame.akde returns akde home-range
contour SpatialPolygons objects from akde object
- new function writeShapefile.akde writes akde home-range contours to
ESRI shapefile
- new function raster.akde returns akde pdf raster object
- new function summary.akde returns HR area of AKDE
- fixed bad CI in plot.telemetry model option
- as.telemetry now takes a timezone argument for as.POSIXct and
defaults to UTC
- telemetry, ctmm, and akde objects now have idenification and
projection information slotted, with consistent naming throughout
ctmm 0.2.0 (2015-04-27)
- vignettes “variogram” and “akde”
- new function as.telemetry imports MoveBank formatted csv data and
returns telemetry objects
- new function variogram.zoom plots a variogram with zoom slider
- variogram.fit and variogram.zoom default to a logarithmic-scale zoom
slider, which requires much less fiddling
- plot.variogram now takes multiple variogram, model, and color
options
- plot.telemetry now takes multiple data, model, akde, and color
options
- plot.telemetry can now make probability density plots for both
Gaussian model and akde data
- ctmm.fit no longer screws up results with initial sigma
guesstimates. ML parameter estimates now match closely with published
Mathematica results. CIs are improved.
- ks-package was producing incorrect home-range contours and has been
replaced with custom code. ML home ranges now match published
Mathematica results. CIs should be improved.