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, RSF-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)
================

  * export bugfixes

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.
