0.1.4

cocons 0.1.4

• Documentation polished

Enhances

• GetNeg2loglikelihood, GetNeg2loglikelihoodTaper, and GetNeg2loglikelihoodTaperProfile now much faster (~35% faster)
• cocoOptim:
  • new REML estimation for dense coco type.
• now cpp functions cov_rns and cov_rns_taper include as special cases the well-known shapes when nu = 0.5, 1.5, and 2.5, yielding computational speed-ups.
• now getCIs display names of covariate instead of index of Design Matrix.
• now .cocons.check.info also checks for smoothness model and smooth.limits.

Changes

• coco now accepts data.frame for locs argument, which is then converted to matrix.
• getTrend now is called getSpatMean.
• cocoPredict renamed output spatial mean vectors: trend is now called systematic, while mean is called stochastic.
• cocoOptim :
  • reordering of arguments.
  • mle estimation method now called ml.
  • pmle estimation method now called pml.
• getHessian :
  • mle to ml and pmle to pml.
• getCIs now alpha argument reflects confidence level instead of 1-confidence level.

Fixes

• fix a bug for plotOptimInfo when handling pml or reml objects.

0.1.3

cocons 0.1.3

• Vignette updates, watermark removed
• Documentation polished
• New holes_bm dataset with independent realizations and spatial trend

Enhances

• added a NEWS.md file with version updates / modifications / enhances / etc
• automatized delta for method plot for coco class.
• Better visualization for plot(cocoOptim object, type = "ellipse")
• coco:
  • now it is not necessary to provide all models for each source of nonstationarity. Those not specified will be set to those referenced
    with a stationary 0-mean model (i.e. tilt = 0 , aniso = 0, nugget = -Inf (because of log-parameterization)). If 'smooth' is not specified, then it is set to 0.5.
• cocoOptim:
  • "auto" option for ncores argument for cocoOptim, providing a convenient number of threads based on the number of parameters to estimate, available threads, and settings of the LBFGSB routine
  • "safe" argument, which prevents crashes due to ill-posed covariance matrices (Choelsky factorization error)
  • .cocons.check.convergence now checks and reports at which iteration ill-posed covariance matrices have been found during the optimization.
  • now "pmle" works with multiple independent realizations for coco types dense and sparse
  • safer parallel handling
• getHessian more memory efficient
• cocoSim:
  • if provided a fitted coco object, then pars argument can be NULL (default), and coco.object@output$par is used instead (and also type is set to diff).
  • more memory efficient
• safer parallel handling for getHessian
• polishing of neg2loglikelihood functions, leading to more efficient code
• new and more polished internal functions to assess the validity of arguments (stopifnot() instead of if() stop())
• getCondNumber optimized
• small improvement over cpp functions

Changes

• switched getPen as an internal function
• method plot for coco objects shows rotation angle of the kernel w.r.t x-axis
• GetSpateffects now provides angle w.r.t to x-axis
• method "summary" for coco objecets (former "print" method)
• more proper naming of objects inside functions
• renaming of "cat.vars" to "skip.scale" + associated checks and optimization
• getCondNumber removed, which can be replaced with kappa function from base R (i.e. kappa(getCovMatrix(coco.object),exact = TRUE))

cocons 0.1.2

Several improves from 0.1.1:

• Improve overall help files
• Add examples for coco, cocoOptim, cocoPredict, and cocoSim
• update Vignette
• some bug fixes and overall code polishing

Some important changes in R files:

• "smooth_limits" of "info" from the coco function is now called "smooth.limits" to match the style of other arguments (no backward compatibility)
• new names for C++ sparse covariance functions
• add warnings of non-convergence of the LBFGSB for cocoOptim
• bug fixes for coco "methods"
• less redundant code