NEWS

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multiScaleR 0.6.30

• Added 'estimate_multiscale_ram()' to report 'kernel_prep()' memory use, conservative parallel RAM budgets, and recommended worker counts based on available RAM and physical CPU cores while reserving two cores

multiScaleR 0.6.29

• Added aggregation index ('ai') as a supported 'landscape_var()' metric, including fixed-buffer, optimized-radius, and FFT raster projection paths with accuracy checks against 'landscapemetrics'
• Hardened 'summary.multiScaleR()' argument handling so optional arguments such as 'prob' and 'profile' are validated consistently
• Clarified screened-start documentation for 'n_cores' and Windows PSOCK behavior, and added real-worker regression coverage

multiScaleR 0.6.28

• Parallelized short screened-start optimization attempts in 'multiScale_optim()' using the same 'n_cores' allocation as the main optimization when 'start_strategy = "screen"'
• Added a serial fallback path if parallel screening fails, and added regression coverage for core allocation behavior in screening

multiScaleR 0.6.27

• Expanded the landscape metric vignette workflow with release-ready examples, including fixed-radius metric projection guidance
• Added optional parallel covariate profiling in 'profile_sigma()' via 'n_cores' and documented practical core-selection guidance in vignettes
• Added regression coverage for standalone fixed-radius landscape metric projection and serial-versus-parallel sigma profile parity

multiScaleR 0.6.26

• Refined optimization diagnostics and next-run restart messaging in 'multiScale_optim()' documentation and tests
• Updated vignette guidance for iterative optimization workflows

multiScaleR 0.6.25

• Added 'next_run' recommendations to 'multiScale_optim()' output with follow-up starting values and a diagnostic-informed 'max_D' suggestion
• Suppressed benign package attach warnings in marginal-effect and PSOCK helper fallback loads so local checks do not fail on R patch-version mismatches alone

multiScaleR 0.6.24

• Corrected 'aic_tab()' roxygen registration so package checks generate the proper help alias and no longer warn about missing documentation entries

multiScaleR 0.6.23

• Added a regression test that asserts the package's expected public exports remain available in the installed namespace

multiScaleR 0.6.22

• Restored missing exports for model-selection and simulation helpers used in package vignettes, including 'aic_tab()', 'bic_tab()', 'sim_rast()', 'sim_dat()', and 'sim_dat_unmarked()'

multiScaleR 0.6.21

• Added an opt-in screened start strategy for 'multiScale_optim()' that scouts sigma values with log-spaced prescreening and short serial screening runs before a single full optimization

multiScaleR 0.6.20

• Hardened 'plot_marginal_effects()' for wrapped/nested fitted models such as 'amt::fit_clogit()'-style objects
• Added regression coverage for marginal effect plots built from nested 'clogit' analysis models

multiScaleR 0.6.19

• Counted one optimized parameter per fitted 'sigma'/shape term in 'aic_tab()', 'bic_tab()', and 'profile_sigma()' AICc calculations
• Rejected AIC/BIC comparisons when models use different observation sets, even if the sample sizes match
• Propagated '.libPaths()' and 'R_LIBS*' settings to PSOCK workers for more reliable project-local parallel optimization on Windows
• Added an 'opt_distance' summary alias alongside the existing 'opt_dist'

multiScaleR 0.6.18

• Reconciled the merged landscape metric branch with a projection fix for fitted models that use only a subset of cached raster covariates
• Added regression coverage for 'kernel_scale.raster()' when stored 'scale_vars' include unused source layers

multiScaleR 0.6.17

• Added a landscape metric covariates vignette demonstrating explicit 'msr_vars()' specifications with 100 spatial sample points
• Linked the quick-start guide to the landscape metric covariate workflow

multiScaleR 0.6.16

• Added 'msr_vars()', 'kernel_var()', and 'landscape_var()' specifications for explicit derived raster covariates
• Allowed multiple covariate transformations, such as kernel means and fixed landscape metrics, to be derived from the same source raster layer
• Added exploratory raster projection support for specified landscape metric covariates

multiScaleR 0.6.15

• Added internal fixed-buffer SHDI helpers for exploratory landscape metric support
• Added FFT-based SHDI raster projection prototype and reference tests
• Added internal fixed-buffer and FFT projection prototypes for edge density
• Expanded exploratory landscape metric helpers to composition/diversity, total edge, landscape shape, percentage-like-adjacency, and contagion metrics
• Added compiled fixed-buffer metric primitives to improve repeated point-level landscape metric calculations
• Added FFT raster projection support for exploratory landscape shape index calculations

multiScaleR 0.6.14

• Improved model-data, predictor, and log-likelihood handling for wrapped model objects
• Added regression coverage for nested 'clogit' wrappers in serial and PSOCK optimization
• Avoided recoverable model-data warnings in marginal effect plots

multiScaleR 0.6.13 (2026-04-18)

• Added a Windows R-devel compatibility shim for Rcpp header compilation

multiScaleR 0.6.12

• Forced C++17 compilation for compatibility with CRAN Windows R-devel checks

multiScaleR 0.6.11

• Fixed PSOCK optimization for unqualified model calls such as 'glm.nb()' after 'library(MASS)'

multiScaleR 0.6.10

• Preserved original sparse kernel dot-product behavior for complete raster layers
• Preserved point row identities across 'kernel_prep()' outputs used during optimization
• Ensured PSOCK workers use the same multiScaleR code as the main R session
• Fixed complete-case row alignment when fitted model frames retain original row names

multiScaleR 0.6.8

• Added linear and user-specified sigma grids to 'profile_sigma()'

multiScaleR 0.6.7

• Fixed singular-Hessian fallback SE values to remain numeric
• Excluded missing raster cells from sparse kernel weighted averages

multiScaleR 0.6.6 (2026-04-13)

• Added an optional custom refit hook for model classes that cannot use default model updates
• Improved internal model refitting and log-likelihood dispatch for broader model support

multiScaleR 0.6.5

• Added structured optimization diagnostics and a 'diagnostics()' accessor
• Fixed complete-case alignment in multiscale optimization inputs
• Updated vignettes and restored 'multiScale_optim()' export handling

multiScaleR 0.6.4

• Added sigma profiling and plot methods
• Expanded plotting tests and updated vignettes
• Streamlined GitHub Actions checks on direct pushes

multiScaleR 0.6.3

• Made profile-likelihood CIs optional in 'summary'
• Updated vignettes and compressed example data

multiScaleR 0.6.2

• Expanded test coverage
• Improved error messaging

multiScaleR 0.6.1

• Fixed test error

multiScaleR 0.6.0

• Added unit testing

multiScaleR 0.5.0 (2026-03-26)

• Updated handling of edge and NA values in 'kernel_scale.raster'
• Updated ‘kernel_scale.raster' to create ’dummy' layers for site effect variables
• Added vignette on spatial projections
• Submitted to CRAN

multiScaleR 0.4.6

• Updated handling of mixed effects models
• Updated error handling

multiScaleR 0.4.5 (2025-09-02)

• Added 'verbose' argument to functions to optionally supress console printing
• Made updates for CRAN checks

multiScaleR 0.4.4

• Updated 'kernel_scale.raster' documentation and clamping defaults

multiScaleR 0.4.3

• Updated handling of zero-infalted models in 'plot_marginal_effects'

multiScaleR 0.4.2

• Update dependencies to pass CRAN checks
• Added hex sticker
• Added 'rhub.yaml'
• Updated to pass CRAN checks

multiScaleR 0.4.1-2

• Updated vignette to demonstrate fitting of zero-inflated model

multiScaleR 0.4.1-1

• Updated 'aic_tab' and 'bic_tab' to properly check model types.
• Fixed bug in 'kernel_scale.raster'

multiScaleR 0.4.1-0

• Updated calculation of cumulative distance
• Added marginal effects plot function 'plot_marginal_effect'
• Updated 'kernel_scale.raster'

multiScaleR 0.4.0-1

• Updated 'sim_rast' for efficiency. Uses custom fft

multiScaleR 0.4.0-0

• Incorporated scaling & centering 'kernel_scale.raster'
• 'scale_opt' is now deprecated in 'kernel_scale.raster'; replaced with 'multiScaleR' argument.
• Updated package data file structure
• Passes CRAN checks

multiScaleR 0.3.1-4

• Updates to better generalize across model classes

multiScaleR 0.3.1-3

• Updated parallel processing handling to generalize use across model classes

multiScaleR 0.3.1-2

• Updated default 'pct_wt' from 0.95 to 0.975 when smoothing raster layers
• Fixed kernel_scale.raster error handling

multiScaleR 0.3.1-1

• Fixed bug in raster smoothing
• Added na.rm argument

multiScaleR 0.3.1-0

• Implemented fft smoothing of rasters
• Removed NLMR and RandomFields dependencies

multiScaleR 0.3.0-5

• Fixed bug causing optimization failure if only a single spatial covariate was used.

multiScaleR 0.3.0-4

• Updated documentation and created a PSOCK variable to force PSOCK cluster when using unix

multiScaleR 0.3.0-3

• Updated variable checks of 'multiScale_optim'
• Removed use of ‘method' and 'opt_parallel' variables. Method is always ’L-BFGS-B' and if cores > 1 is specified, parallelization is implicit.

multiScaleR 0.3.0-2

• Uses sparse matrices for reduced memory demands

multiScaleR 0.3.0-1

• Updated kernel density functions to c++ for speed

multiScaleR 0.2.0-8

• Updated parallelization to use forking when operating on a Unix OS
• Updated DESCRIPTION file to reflect necessary dependencies

multiScaleR 0.2.0-7

• Updated simulation function to create repeat sampling data
• Updated vignette to demonstrate use of 'multiScaleR' with 'unmarked'.

multiScaleR 0.2.0-6

• Bug fixes
• Added 'join_by' command when optimizing 'unmarked' models with stacked data formats

multiScaleR 0.2.0-3

• Updated error handling across core functions

multiScaleR 0.2.0-2

• Fixed bug preventing optimization using unmarked models

multiScaleR 0.2.0-1

• Modified formatting of vignette document

multiScaleR 0.2.0

• Modified 'multiScaleR_optim' to reduce size of final optimized object.
• Completed vignette: use 'build_vignettes = TRUE' when installing
• Updated code to accomodate lme4 and other model classes supported by 'insight' package.

multiScaleR 0.1.5

• Updated plot function to show 95% confidence interval of scale of effect distance
• Updated summary function to report mean and 95% scale of effect distance
• Updated example data included with package to demonstrate more extensive use of package
• Future addition -- A vignette demonstrating the use of the package

multiScaleR 0.1.4

• Cleaned code
• Added documentation and examples to 'multiScale_optim'

multiScaleR 0.1.3

• Corrected issue with distance weighting function
• Updated how parameters are scaled

multiScaleR 0.1.2

• Fixed bug in optimization function

multiScaleR 0.1.1

• Fixed trap that was causing optimization with 'fixed' and 'expow' to fail
• Updated plot and kernel_dist functions

multiScaleR 0.1.0

• Initial commit. Bugs and issues present, needed for class