• 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
  • 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()
  • 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.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
  • 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()
  • as.telemetry() location class code improved
  • as.telemetry() message for marked outliers
  • jaguar data in sync with ctmmweb
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • projection method for ctmm objects
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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”
  • 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
  • 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
  • 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
  • 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
  • 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
  • export bugfixes
  • IOU bug fixes in ctmm.fit and plot.variogram
  • 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
  • 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
  • new functions periodogram, plot.periodogram
  • 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
  • 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.